Igor Lins e Silva
9dd56ecb0a
#1262 split `get_or_create_collection` into `get_collection` + fallback `create_collection` inside `ChromaBackend.get_collection`, fixing the chromadb 1.5.x Rust-binding SIGSEGV that fires when stored collection metadata differs from the call-site's `_HNSW_BLOAT_GUARD` payload. The MCP server's `_get_collection(create=True)` carries the same metadata payload at `mcp_server.py:287` and routes through chromadb's Python client directly, bypassing the backend layer. Both `tool_add_drawer` and `tool_diary_write` reach this site on every invocation, and the Stop hook fires `mempalace_diary_write` at session end — which was exactly the crash path #1089 named. Apply the same try/except split here so legacy palaces whose stored metadata predates the bloat-guard expansion no longer crash on the MCP-server reopen path. Regression test patches `get_or_create_collection` at the chromadb client class level (not the instance — chromadb's mtime-change detection rebuilds the client between calls, so an instance-level spy doesn't survive) and asserts the second `_get_collection(create=True)` call never reaches it.
1950 lines
71 KiB
Python
1950 lines
71 KiB
Python
#!/usr/bin/env python3
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"""
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MemPalace MCP Server — read/write palace access for Claude Code
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================================================================
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Install: claude mcp add mempalace -- mempalace-mcp [--palace /path/to/palace]
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Tools (read):
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mempalace_status — total drawers, wing/room breakdown
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mempalace_list_wings — all wings with drawer counts
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mempalace_list_rooms — rooms within a wing
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mempalace_get_taxonomy — full wing → room → count tree
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mempalace_search — semantic search, optional wing/room filter
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mempalace_check_duplicate — check if content already exists before filing
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Tools (write):
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mempalace_add_drawer — file verbatim content into a wing/room
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mempalace_delete_drawer — remove a drawer by ID
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Tools (maintenance):
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mempalace_reconnect — force cache invalidation and reconnect after external writes
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"""
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import os
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import sys
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# --- MCP stdio protection (issue #225) -----------------------------------
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# The MCP protocol multiplexes JSON-RPC over stdio: stdout MUST carry only
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# valid JSON-RPC messages, stderr is for human-readable logs. Some
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# transitive dependencies (chromadb → onnxruntime, posthog telemetry) print
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# banners and error messages directly to stdout — sometimes at C level —
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# which breaks Claude Desktop's JSON parser. Redirect stdout → stderr at
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# both the Python and file-descriptor level before heavy imports, then
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# restore the real stdout in main() before entering the protocol loop.
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_REAL_STDOUT = sys.stdout
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_REAL_STDOUT_FD = None
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try:
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_REAL_STDOUT_FD = os.dup(1)
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os.dup2(2, 1)
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except (OSError, AttributeError):
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# Environments without fd-level stdio (embedded interpreters, some test
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# harnesses). The Python-level redirect below still applies.
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pass
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sys.stdout = sys.stderr
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import argparse # noqa: E402 (deferred until after stdio protection above)
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import json # noqa: E402
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import logging # noqa: E402
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import hashlib # noqa: E402
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import time # noqa: E402
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from datetime import datetime # noqa: E402
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from pathlib import Path # noqa: E402
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from .config import ( # noqa: E402
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MempalaceConfig,
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sanitize_kg_value,
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sanitize_name,
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sanitize_content,
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)
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from .version import __version__ # noqa: E402
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from chromadb.errors import NotFoundError as _ChromaNotFoundError # noqa: E402
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from .backends.chroma import ( # noqa: E402
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ChromaBackend,
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ChromaCollection,
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_HNSW_BLOAT_GUARD,
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_pin_hnsw_threads,
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hnsw_capacity_status,
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)
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from .query_sanitizer import sanitize_query # noqa: E402
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from .searcher import search_memories # noqa: E402
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from .palace_graph import ( # noqa: E402
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traverse,
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find_tunnels,
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graph_stats,
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create_tunnel,
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list_tunnels,
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delete_tunnel,
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follow_tunnels,
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)
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from .knowledge_graph import KnowledgeGraph # noqa: E402
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logging.basicConfig(level=logging.INFO, format="%(message)s", stream=sys.stderr)
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logger = logging.getLogger("mempalace_mcp")
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def _parse_args():
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parser = argparse.ArgumentParser(description="MemPalace MCP Server")
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parser.add_argument(
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"--palace",
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metavar="PATH",
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help="Path to the palace directory (overrides config file and env var)",
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)
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args, unknown = parser.parse_known_args()
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if unknown:
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logger.debug("Ignoring unknown args: %s", unknown)
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return args
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_args = _parse_args()
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if _args.palace:
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os.environ["MEMPALACE_PALACE_PATH"] = os.path.abspath(_args.palace)
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_config = MempalaceConfig()
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# Only override KG path when --palace is explicitly provided; otherwise use
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# KnowledgeGraph's default (~/.mempalace/knowledge_graph.sqlite3).
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if _args.palace:
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_kg = KnowledgeGraph(db_path=os.path.join(_config.palace_path, "knowledge_graph.sqlite3"))
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else:
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_kg = KnowledgeGraph()
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_client_cache = None
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_collection_cache = None
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_palace_db_inode = 0 # inode of chroma.sqlite3 at cache time
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_palace_db_mtime = 0.0 # mtime of chroma.sqlite3 at cache time
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# ── Vector-search disabled flag (#1222) ──────────────────────────────────
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# Set when ``hnsw_capacity_status`` reports a divergence between sqlite
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# and the HNSW segment large enough that chromadb would segfault on
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# segment load. While this is set, vector-shaped tools (``search``,
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# ``check_duplicate``) route to the sqlite-only BM25 fallback in
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# :func:`mempalace.searcher._bm25_only_via_sqlite`. Cleared after a
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# successful repair via :func:`tool_reconnect` (which re-runs the probe).
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_vector_disabled = False
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_vector_disabled_reason = ""
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# Optional[dict] (not ``dict | None``) keeps Python 3.9 import-time
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# parsing happy — PEP 604 unions in annotations only became unconditional
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# at module-eval time in 3.10.
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_vector_capacity_status = None # type: Optional[dict]
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def _refresh_vector_disabled_flag() -> None:
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"""Re-run the HNSW capacity probe and update the module-level flag.
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Called from :func:`_get_client` whenever the client cache is rebuilt
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(first open or palace replacement). Cheap — pure sqlite + pickle
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read, no chromadb interaction. Never raises: a probe that crashes
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would defeat the point.
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"""
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global _vector_disabled, _vector_disabled_reason, _vector_capacity_status
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try:
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info = hnsw_capacity_status(_config.palace_path, "mempalace_drawers")
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except Exception:
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logger.debug("HNSW capacity probe raised", exc_info=True)
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return
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_vector_capacity_status = info
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if info.get("diverged"):
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if not _vector_disabled:
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logger.warning(
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"HNSW capacity divergence detected (%s) — routing search to "
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"BM25-only sqlite fallback. Run `mempalace repair` to restore "
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"vector search.",
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info.get("message", "unknown"),
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)
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_vector_disabled = True
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_vector_disabled_reason = info.get("message", "")
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else:
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if _vector_disabled:
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logger.info(
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"HNSW capacity within tolerance (%s) — vector search re-enabled",
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info.get("message", ""),
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)
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_vector_disabled = False
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_vector_disabled_reason = ""
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# ==================== WRITE-AHEAD LOG ====================
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# Every write operation is logged to a JSONL file before execution.
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# This provides an audit trail for detecting memory poisoning and
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# enables review/rollback of writes from external or untrusted sources.
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_WAL_DIR = Path(os.path.expanduser("~/.mempalace/wal"))
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_WAL_DIR.mkdir(parents=True, exist_ok=True)
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try:
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_WAL_DIR.chmod(0o700)
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except (OSError, NotImplementedError):
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pass
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_WAL_FILE = _WAL_DIR / "write_log.jsonl"
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# Atomically create WAL file with restricted permissions (no TOCTOU race).
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# os.open with O_CREAT|O_WRONLY and mode 0o600 creates the file if absent
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# or opens it if present, both in a single syscall.
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try:
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_fd = os.open(str(_WAL_FILE), os.O_CREAT | os.O_WRONLY, 0o600)
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os.close(_fd)
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except (OSError, NotImplementedError):
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pass
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# Keys whose values should be redacted in WAL entries to avoid logging sensitive content
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_WAL_REDACT_KEYS = frozenset(
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{"content", "content_preview", "document", "entry", "entry_preview", "query", "text"}
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)
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def _wal_log(operation: str, params: dict, result: dict = None):
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"""Append a write operation to the write-ahead log."""
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# Redact sensitive content from params before logging
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safe_params = {}
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for k, v in params.items():
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if k in _WAL_REDACT_KEYS:
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safe_params[k] = f"[REDACTED {len(v)} chars]" if isinstance(v, str) else "[REDACTED]"
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else:
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safe_params[k] = v
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entry = {
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"timestamp": datetime.now().isoformat(),
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"operation": operation,
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"params": safe_params,
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"result": result,
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}
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try:
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fd = os.open(str(_WAL_FILE), os.O_WRONLY | os.O_APPEND | os.O_CREAT, 0o600)
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with os.fdopen(fd, "a", encoding="utf-8") as f:
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f.write(json.dumps(entry, default=str) + "\n")
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except Exception as e:
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logger.error(f"WAL write failed: {e}")
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def _get_client():
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"""Return a ChromaDB PersistentClient, reconnecting if the database changed on disk.
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Detects palace rebuilds (repair/nuke/purge) by checking the inode of
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chroma.sqlite3. A full rebuild replaces the file, changing the inode.
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Also detects external writes (scripts, CLI) via mtime changes — the
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inode check alone misses in-place modifications that invalidate the
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in-memory HNSW index.
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Note: FAT/exFAT may return 0 for st_ino — the ``current_inode != 0``
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guard skips reconnect detection on those filesystems (safe fallback).
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"""
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global \
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_client_cache, \
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_collection_cache, \
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_palace_db_inode, \
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_palace_db_mtime, \
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_metadata_cache, \
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_metadata_cache_time
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db_path = os.path.join(_config.palace_path, "chroma.sqlite3")
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try:
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st = os.stat(db_path)
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current_inode = st.st_ino
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current_mtime = st.st_mtime
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except OSError:
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current_inode = 0
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current_mtime = 0.0
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# If the DB file disappeared (e.g. during rebuild) but we have a cached
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# collection, invalidate so we don't serve stale data. Without this,
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# both stored and current values are 0 on the first call after deletion,
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# making inode_changed and mtime_changed both False.
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if not os.path.isfile(db_path) and _collection_cache is not None:
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_client_cache = None
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_collection_cache = None
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_palace_db_inode = 0
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_palace_db_mtime = 0.0
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# Fall through to normal reconnect which will handle missing DB
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inode_changed = current_inode != 0 and current_inode != _palace_db_inode
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mtime_changed = current_mtime != 0.0 and abs(current_mtime - _palace_db_mtime) > 0.01
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if _client_cache is None or inode_changed or mtime_changed:
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# Run the HNSW capacity probe BEFORE chromadb opens the segment —
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# if the index is severely undersized, segment load can segfault
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# the whole MCP server (#1222). The probe is pure sqlite +
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# metadata-pickle read; never touches the HNSW binary files.
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_refresh_vector_disabled_flag()
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_client_cache = ChromaBackend.make_client(_config.palace_path)
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_collection_cache = None
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_metadata_cache = None
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_metadata_cache_time = 0
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_palace_db_inode = current_inode
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_palace_db_mtime = current_mtime
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return _client_cache
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def _get_collection(create=False):
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"""Return the ChromaDB collection, caching the client between calls."""
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global _collection_cache, _metadata_cache, _metadata_cache_time
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try:
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client = _get_client()
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if create:
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# hnsw:num_threads=1 disables ChromaDB's multi-threaded ParallelFor
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# HNSW insert path, which has a race in repairConnectionsForUpdate /
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# addPoint (see issues #974, #965). Set via metadata on fresh
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# collections and re-applied via _pin_hnsw_threads() for legacy
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# palaces whose collections were created before this fix (the
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# runtime config does not persist cross-process in chromadb 1.5.x,
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# so the retrofit runs every time _get_collection opens a cache).
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#
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# ChromaDB 1.5.x's Rust binding SIGSEGVs when get_or_create_collection
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# is called with metadata that differs from what's stored. The split
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# below skips the metadata-comparison codepath for existing
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# collections, mirroring the backend-layer fix from #1262.
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try:
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raw = client.get_collection(_config.collection_name)
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except _ChromaNotFoundError:
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raw = client.create_collection(
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_config.collection_name,
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metadata={
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"hnsw:space": "cosine",
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"hnsw:num_threads": 1,
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**_HNSW_BLOAT_GUARD,
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},
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)
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_pin_hnsw_threads(raw)
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_collection_cache = ChromaCollection(raw)
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_metadata_cache = None
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_metadata_cache_time = 0
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elif _collection_cache is None:
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raw = client.get_collection(_config.collection_name)
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_pin_hnsw_threads(raw)
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_collection_cache = ChromaCollection(raw)
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_metadata_cache = None
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_metadata_cache_time = 0
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return _collection_cache
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except Exception:
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return None
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def _no_palace():
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return {
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"error": "No palace found",
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"hint": "Run: mempalace init <dir> && mempalace mine <dir>",
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}
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# ==================== HELPERS ====================
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def _fetch_all_metadata(col, where=None):
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"""Paginate col.get() to avoid the 10K silent truncation limit."""
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total = col.count()
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all_meta = []
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offset = 0
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while offset < total:
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kwargs = {"include": ["metadatas"], "limit": 1000, "offset": offset}
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if where:
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kwargs["where"] = where
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batch = col.get(**kwargs)
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if not batch["metadatas"]:
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break
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all_meta.extend(batch["metadatas"])
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offset += len(batch["metadatas"])
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return all_meta
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_metadata_cache = None
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_metadata_cache_time = 0
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_METADATA_CACHE_TTL = 5.0 # seconds
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_MAX_RESULTS = 100 # upper bound for search/list limit params
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def _get_cached_metadata(col, where=None):
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"""Return cached metadata if fresh, else fetch and cache."""
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global _metadata_cache, _metadata_cache_time
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now = time.time()
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if (
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where is None
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and _metadata_cache is not None
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and (now - _metadata_cache_time) < _METADATA_CACHE_TTL
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):
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return _metadata_cache
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result = _fetch_all_metadata(col, where=where)
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if where is None:
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_metadata_cache = result
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_metadata_cache_time = now
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return result
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def _sanitize_optional_name(value: str = None, field_name: str = "name") -> str:
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"""Validate optional wing/room-style filters."""
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if value is None or not value.strip():
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return None
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return sanitize_name(value, field_name)
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# ==================== READ TOOLS ====================
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def _tool_status_via_sqlite() -> dict:
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"""Pure-sqlite status reader for the #1222 fallback path.
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When the HNSW capacity probe detects divergence, opening the chromadb
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persistent client can segfault. This reader pulls the same wing/room
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breakdown directly from ``embedding_metadata`` so the operator still
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gets a working status response — and crucially the
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``vector_disabled`` flag — without us touching the vector segment.
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"""
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import sqlite3 as _sqlite3
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db_path = os.path.join(_config.palace_path, "chroma.sqlite3")
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if not os.path.isfile(db_path):
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return _no_palace()
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wings: dict = {}
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rooms: dict = {}
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total = 0
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try:
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conn = _sqlite3.connect(f"file:{db_path}?mode=ro", uri=True)
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try:
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row = conn.execute(
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"""
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SELECT COUNT(*)
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FROM embeddings e
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JOIN segments s ON e.segment_id = s.id
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JOIN collections c ON s.collection = c.id
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WHERE c.name = 'mempalace_drawers'
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"""
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).fetchone()
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total = int(row[0]) if row and row[0] is not None else 0
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for key, target in (("wing", wings), ("room", rooms)):
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for value, count in conn.execute(
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"""
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SELECT em.string_value, COUNT(*)
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FROM embedding_metadata em
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JOIN embeddings e ON em.id = e.id
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JOIN segments s ON e.segment_id = s.id
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JOIN collections c ON s.collection = c.id
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WHERE c.name = 'mempalace_drawers'
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AND em.key = ?
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AND em.string_value IS NOT NULL
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GROUP BY em.string_value
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""",
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(key,),
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):
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target[value] = count
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finally:
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conn.close()
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except _sqlite3.Error:
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logger.exception("tool_status sqlite fallback read failed")
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result = {
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"total_drawers": total,
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"wings": wings,
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"rooms": rooms,
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"palace_path": _config.palace_path,
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"protocol": PALACE_PROTOCOL,
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"aaak_dialect": AAAK_SPEC,
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"vector_disabled": True,
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"vector_disabled_reason": _vector_disabled_reason,
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}
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if _vector_capacity_status:
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result["hnsw_capacity"] = {
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"sqlite_count": _vector_capacity_status.get("sqlite_count"),
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"hnsw_count": _vector_capacity_status.get("hnsw_count"),
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"divergence": _vector_capacity_status.get("divergence"),
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}
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return result
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def tool_status():
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# Run the safe sqlite/pickle probe before we touch chromadb. In the
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# #1222 failure mode, opening the persistent client to call .count()
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# can segfault — short-circuit to a pure-sqlite path when divergence
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# is detected so status stays reachable.
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db_exists = os.path.isfile(os.path.join(_config.palace_path, "chroma.sqlite3"))
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_refresh_vector_disabled_flag()
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if _vector_disabled:
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return _tool_status_via_sqlite()
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# Use create=True only when a palace DB already exists on disk -- this
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# bootstraps the ChromaDB collection on a valid-but-empty palace without
|
|
# accidentally creating a palace in a non-existent directory (#830).
|
|
col = _get_collection(create=db_exists)
|
|
if not col:
|
|
return _no_palace()
|
|
count = col.count()
|
|
wings = {}
|
|
rooms = {}
|
|
result = {
|
|
"total_drawers": count,
|
|
"wings": wings,
|
|
"rooms": rooms,
|
|
"palace_path": _config.palace_path,
|
|
"protocol": PALACE_PROTOCOL,
|
|
"aaak_dialect": AAAK_SPEC,
|
|
}
|
|
try:
|
|
all_meta = _get_cached_metadata(col)
|
|
for m in all_meta:
|
|
m = m or {}
|
|
w = m.get("wing", "unknown")
|
|
r = m.get("room", "unknown")
|
|
wings[w] = wings.get(w, 0) + 1
|
|
rooms[r] = rooms.get(r, 0) + 1
|
|
except Exception as e:
|
|
logger.exception("tool_status metadata fetch failed")
|
|
result["error"] = str(e)
|
|
result["partial"] = True
|
|
return result
|
|
|
|
|
|
# ── AAAK Dialect Spec ─────────────────────────────────────────────────────────
|
|
# Included in status response so the AI learns it on first wake-up call.
|
|
# Also available via mempalace_get_aaak_spec tool.
|
|
|
|
PALACE_PROTOCOL = """IMPORTANT — MemPalace Memory Protocol:
|
|
1. ON WAKE-UP: Call mempalace_status to load palace overview + AAAK spec.
|
|
2. BEFORE RESPONDING about any person, project, or past event: call mempalace_kg_query or mempalace_search FIRST. Never guess — verify.
|
|
3. IF UNSURE about a fact (name, gender, age, relationship): say "let me check" and query the palace. Wrong is worse than slow.
|
|
4. AFTER EACH SESSION: call mempalace_diary_write to record what happened, what you learned, what matters.
|
|
5. WHEN FACTS CHANGE: call mempalace_kg_invalidate on the old fact, mempalace_kg_add for the new one.
|
|
|
|
This protocol ensures the AI KNOWS before it speaks. Storage is not memory — but storage + this protocol = memory."""
|
|
|
|
AAAK_SPEC = """AAAK is a compressed memory dialect that MemPalace uses for efficient storage.
|
|
It is designed to be readable by both humans and LLMs without decoding.
|
|
|
|
FORMAT:
|
|
ENTITIES: 3-letter uppercase codes. ALC=Alice, JOR=Jordan, RIL=Riley, MAX=Max, BEN=Ben.
|
|
EMOTIONS: *action markers* before/during text. *warm*=joy, *fierce*=determined, *raw*=vulnerable, *bloom*=tenderness.
|
|
STRUCTURE: Pipe-separated fields. FAM: family | PROJ: projects | ⚠: warnings/reminders.
|
|
DATES: ISO format (2026-03-31). COUNTS: Nx = N mentions (e.g., 570x).
|
|
IMPORTANCE: ★ to ★★★★★ (1-5 scale).
|
|
HALLS: hall_facts, hall_events, hall_discoveries, hall_preferences, hall_advice.
|
|
WINGS: wing_user, wing_agent, wing_team, wing_code, wing_myproject, wing_hardware, wing_ue5, wing_ai_research.
|
|
ROOMS: Hyphenated slugs representing named ideas (e.g., chromadb-setup, gpu-pricing).
|
|
|
|
EXAMPLE:
|
|
FAM: ALC→♡JOR | 2D(kids): RIL(18,sports) MAX(11,chess+swimming) | BEN(contributor)
|
|
|
|
Read AAAK naturally — expand codes mentally, treat *markers* as emotional context.
|
|
When WRITING AAAK: use entity codes, mark emotions, keep structure tight."""
|
|
|
|
|
|
def tool_list_wings():
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
wings = {}
|
|
result = {"wings": wings}
|
|
try:
|
|
all_meta = _get_cached_metadata(col)
|
|
for m in all_meta:
|
|
m = m or {}
|
|
w = m.get("wing", "unknown")
|
|
wings[w] = wings.get(w, 0) + 1
|
|
except Exception as e:
|
|
logger.exception("tool_list_wings metadata fetch failed")
|
|
result["error"] = str(e)
|
|
result["partial"] = True
|
|
return result
|
|
|
|
|
|
def tool_list_rooms(wing: str = None):
|
|
try:
|
|
wing = _sanitize_optional_name(wing, "wing")
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
rooms = {}
|
|
result = {"wing": wing or "all", "rooms": rooms}
|
|
try:
|
|
where = {"wing": wing} if wing else None
|
|
all_meta = _fetch_all_metadata(col, where=where)
|
|
for m in all_meta:
|
|
m = m or {}
|
|
r = m.get("room", "unknown")
|
|
rooms[r] = rooms.get(r, 0) + 1
|
|
except Exception as e:
|
|
logger.exception("tool_list_rooms metadata fetch failed")
|
|
result["error"] = str(e)
|
|
result["partial"] = True
|
|
return result
|
|
|
|
|
|
def tool_get_taxonomy():
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
taxonomy = {}
|
|
result = {"taxonomy": taxonomy}
|
|
try:
|
|
all_meta = _get_cached_metadata(col)
|
|
for m in all_meta:
|
|
m = m or {}
|
|
w = m.get("wing", "unknown")
|
|
r = m.get("room", "unknown")
|
|
if w not in taxonomy:
|
|
taxonomy[w] = {}
|
|
taxonomy[w][r] = taxonomy[w].get(r, 0) + 1
|
|
except Exception as e:
|
|
logger.exception("tool_get_taxonomy metadata fetch failed")
|
|
result["error"] = str(e)
|
|
result["partial"] = True
|
|
return result
|
|
|
|
|
|
def tool_search(
|
|
query: str,
|
|
limit: int = 5,
|
|
wing: str = None,
|
|
room: str = None,
|
|
max_distance: float = 1.5,
|
|
min_similarity: float = None,
|
|
context: str = None,
|
|
):
|
|
limit = max(1, min(limit, _MAX_RESULTS))
|
|
try:
|
|
wing = _sanitize_optional_name(wing, "wing")
|
|
room = _sanitize_optional_name(room, "room")
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
# Backwards compat: accept old name
|
|
# Backwards compat: convert old similarity scale (higher=stricter) to
|
|
# distance scale (lower=stricter). Similarity 0.8 → distance 0.2.
|
|
dist = (1.0 - min_similarity) if min_similarity is not None else max_distance
|
|
# Mitigate system prompt contamination (Issue #333)
|
|
sanitized = sanitize_query(query)
|
|
# Ensure the vector-disabled probe has been run via the safe
|
|
# sqlite/pickle path before we touch chromadb. Calling _get_client()
|
|
# here would defeat the fallback — it constructs a PersistentClient
|
|
# which can segfault on segment load in the #1222 failure mode.
|
|
_refresh_vector_disabled_flag()
|
|
result = search_memories(
|
|
sanitized["clean_query"],
|
|
palace_path=_config.palace_path,
|
|
wing=wing,
|
|
room=room,
|
|
n_results=limit,
|
|
max_distance=dist,
|
|
vector_disabled=_vector_disabled,
|
|
)
|
|
if _vector_disabled:
|
|
result["vector_disabled"] = True
|
|
result["vector_disabled_reason"] = _vector_disabled_reason
|
|
# Attach sanitizer metadata for transparency
|
|
if sanitized["was_sanitized"]:
|
|
result["query_sanitized"] = True
|
|
result["sanitizer"] = {
|
|
"method": sanitized["method"],
|
|
"original_length": sanitized["original_length"],
|
|
"clean_length": sanitized["clean_length"],
|
|
"clean_query": sanitized["clean_query"],
|
|
}
|
|
if context:
|
|
result["context_received"] = True
|
|
return result
|
|
|
|
|
|
def tool_check_duplicate(content: str, threshold: float = 0.9):
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
if _vector_disabled:
|
|
# Without a usable HNSW we can't compute cosine similarity for
|
|
# near-duplicate detection. Report the limitation rather than
|
|
# silently returning "not a duplicate" — false negatives here
|
|
# would let the AI re-file content the palace already holds.
|
|
return {
|
|
"is_duplicate": False,
|
|
"matches": [],
|
|
"vector_disabled": True,
|
|
"vector_disabled_reason": _vector_disabled_reason,
|
|
"hint": (
|
|
"duplicate detection requires vector search; run " "`mempalace repair` to restore"
|
|
),
|
|
}
|
|
try:
|
|
results = col.query(
|
|
query_texts=[content],
|
|
n_results=5,
|
|
include=["metadatas", "documents", "distances"],
|
|
)
|
|
duplicates = []
|
|
if results["ids"] and results["ids"][0]:
|
|
for i, drawer_id in enumerate(results["ids"][0]):
|
|
dist = results["distances"][0][i]
|
|
similarity = round(1 - dist, 3)
|
|
if similarity >= threshold:
|
|
meta = results["metadatas"][0][i]
|
|
doc = results["documents"][0][i]
|
|
duplicates.append(
|
|
{
|
|
"id": drawer_id,
|
|
"wing": meta.get("wing", "?"),
|
|
"room": meta.get("room", "?"),
|
|
"similarity": similarity,
|
|
"content": doc[:200] + "..." if len(doc) > 200 else doc,
|
|
}
|
|
)
|
|
return {
|
|
"is_duplicate": len(duplicates) > 0,
|
|
"matches": duplicates,
|
|
}
|
|
except Exception:
|
|
logger.exception("check_duplicate failed")
|
|
return {"error": "Duplicate check failed"}
|
|
|
|
|
|
def tool_get_aaak_spec():
|
|
"""Return the AAAK dialect specification."""
|
|
return {"aaak_spec": AAAK_SPEC}
|
|
|
|
|
|
def tool_traverse_graph(start_room: str, max_hops: int = 2):
|
|
"""Walk the palace graph from a room. Find connected ideas across wings."""
|
|
max_hops = max(1, min(max_hops, 10))
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
return traverse(start_room, col=col, max_hops=max_hops)
|
|
|
|
|
|
def tool_find_tunnels(wing_a: str = None, wing_b: str = None):
|
|
"""Find rooms that bridge two wings — the hallways connecting domains."""
|
|
try:
|
|
wing_a = _sanitize_optional_name(wing_a, "wing_a")
|
|
wing_b = _sanitize_optional_name(wing_b, "wing_b")
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
return find_tunnels(wing_a, wing_b, col=col)
|
|
|
|
|
|
def tool_graph_stats():
|
|
"""Palace graph overview: nodes, tunnels, edges, connectivity."""
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
return graph_stats(col=col)
|
|
|
|
|
|
def tool_create_tunnel(
|
|
source_wing: str,
|
|
source_room: str,
|
|
target_wing: str,
|
|
target_room: str,
|
|
label: str = "",
|
|
source_drawer_id: str = None,
|
|
target_drawer_id: str = None,
|
|
):
|
|
"""Create an explicit cross-wing tunnel between two palace locations.
|
|
|
|
Use when you notice content in one project relates to another project.
|
|
Example: an API design discussion in project_api connects to the
|
|
database schema in project_database.
|
|
"""
|
|
try:
|
|
source_wing = sanitize_name(source_wing, "source_wing")
|
|
source_room = sanitize_name(source_room, "source_room")
|
|
target_wing = sanitize_name(target_wing, "target_wing")
|
|
target_room = sanitize_name(target_room, "target_room")
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
return create_tunnel(
|
|
source_wing,
|
|
source_room,
|
|
target_wing,
|
|
target_room,
|
|
label=label,
|
|
source_drawer_id=source_drawer_id,
|
|
target_drawer_id=target_drawer_id,
|
|
)
|
|
|
|
|
|
def tool_list_tunnels(wing: str = None):
|
|
"""List all explicit cross-wing tunnels, optionally filtered by wing."""
|
|
try:
|
|
wing = _sanitize_optional_name(wing, "wing")
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
return list_tunnels(wing)
|
|
|
|
|
|
def tool_delete_tunnel(tunnel_id: str):
|
|
"""Delete an explicit tunnel by its ID."""
|
|
if not tunnel_id or not isinstance(tunnel_id, str):
|
|
return {"error": "tunnel_id is required"}
|
|
return delete_tunnel(tunnel_id)
|
|
|
|
|
|
def tool_follow_tunnels(wing: str, room: str):
|
|
"""Follow explicit tunnels from a room to see connected drawers in other wings."""
|
|
try:
|
|
wing = sanitize_name(wing, "wing")
|
|
room = sanitize_name(room, "room")
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
col = _get_collection()
|
|
return follow_tunnels(wing, room, col=col)
|
|
|
|
|
|
# ==================== WRITE TOOLS ====================
|
|
|
|
|
|
def tool_add_drawer(
|
|
wing: str, room: str, content: str, source_file: str = None, added_by: str = "mcp"
|
|
):
|
|
"""File verbatim content into a wing/room. Checks for duplicates first."""
|
|
global _metadata_cache
|
|
try:
|
|
wing = sanitize_name(wing, "wing")
|
|
room = sanitize_name(room, "room")
|
|
content = sanitize_content(content)
|
|
except ValueError as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
col = _get_collection(create=True)
|
|
if not col:
|
|
return _no_palace()
|
|
|
|
drawer_id = (
|
|
f"drawer_{wing}_{room}_{hashlib.sha256((wing + room + content).encode()).hexdigest()[:24]}"
|
|
)
|
|
|
|
_wal_log(
|
|
"add_drawer",
|
|
{
|
|
"drawer_id": drawer_id,
|
|
"wing": wing,
|
|
"room": room,
|
|
"added_by": added_by,
|
|
"content_length": len(content),
|
|
"content_preview": content[:200],
|
|
},
|
|
)
|
|
|
|
# Idempotency: if the deterministic ID already exists, return success as a no-op.
|
|
try:
|
|
existing = col.get(ids=[drawer_id])
|
|
if existing and existing["ids"]:
|
|
return {"success": True, "reason": "already_exists", "drawer_id": drawer_id}
|
|
except Exception:
|
|
pass
|
|
|
|
try:
|
|
col.upsert(
|
|
ids=[drawer_id],
|
|
documents=[content],
|
|
metadatas=[
|
|
{
|
|
"wing": wing,
|
|
"room": room,
|
|
"source_file": source_file or "",
|
|
"chunk_index": 0,
|
|
"added_by": added_by,
|
|
"filed_at": datetime.now().isoformat(),
|
|
}
|
|
],
|
|
)
|
|
_metadata_cache = None
|
|
logger.info(f"Filed drawer: {drawer_id} → {wing}/{room}")
|
|
return {"success": True, "drawer_id": drawer_id, "wing": wing, "room": room}
|
|
except Exception as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
|
|
def tool_delete_drawer(drawer_id: str):
|
|
"""Delete a single drawer by ID."""
|
|
global _metadata_cache
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
existing = col.get(ids=[drawer_id])
|
|
if not existing["ids"]:
|
|
return {"success": False, "error": f"Drawer not found: {drawer_id}"}
|
|
|
|
# Log the deletion with the content being removed for audit trail
|
|
deleted_content = existing.get("documents", [""])[0] if existing.get("documents") else ""
|
|
deleted_meta = existing.get("metadatas", [{}])[0] if existing.get("metadatas") else {}
|
|
_wal_log(
|
|
"delete_drawer",
|
|
{
|
|
"drawer_id": drawer_id,
|
|
"deleted_meta": deleted_meta,
|
|
"content_preview": deleted_content[:200],
|
|
},
|
|
)
|
|
|
|
try:
|
|
col.delete(ids=[drawer_id])
|
|
_metadata_cache = None
|
|
logger.info(f"Deleted drawer: {drawer_id}")
|
|
return {"success": True, "drawer_id": drawer_id}
|
|
except Exception as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
|
|
def tool_get_drawer(drawer_id: str):
|
|
"""Fetch a single drawer by ID. Returns full content and metadata."""
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
try:
|
|
result = col.get(ids=[drawer_id], include=["documents", "metadatas"])
|
|
if not result["ids"]:
|
|
return {"error": f"Drawer not found: {drawer_id}"}
|
|
meta = result["metadatas"][0]
|
|
doc = result["documents"][0]
|
|
return {
|
|
"drawer_id": drawer_id,
|
|
"content": doc,
|
|
"wing": meta.get("wing", ""),
|
|
"room": meta.get("room", ""),
|
|
"metadata": meta,
|
|
}
|
|
except Exception as e:
|
|
return {"error": str(e)}
|
|
|
|
|
|
def tool_list_drawers(wing: str = None, room: str = None, limit: int = 20, offset: int = 0):
|
|
"""List drawers with pagination. Optional wing/room filter."""
|
|
limit = max(1, min(limit, _MAX_RESULTS))
|
|
offset = max(0, offset)
|
|
try:
|
|
wing = _sanitize_optional_name(wing, "wing")
|
|
room = _sanitize_optional_name(room, "room")
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
try:
|
|
where = None
|
|
conditions = []
|
|
if wing:
|
|
conditions.append({"wing": wing})
|
|
if room:
|
|
conditions.append({"room": room})
|
|
if len(conditions) == 1:
|
|
where = conditions[0]
|
|
elif len(conditions) > 1:
|
|
where = {"$and": conditions}
|
|
|
|
kwargs = {"include": ["documents", "metadatas"], "limit": limit, "offset": offset}
|
|
if where:
|
|
kwargs["where"] = where
|
|
result = col.get(**kwargs)
|
|
|
|
drawers = []
|
|
for i, did in enumerate(result["ids"]):
|
|
meta = result["metadatas"][i]
|
|
doc = result["documents"][i]
|
|
drawers.append(
|
|
{
|
|
"drawer_id": did,
|
|
"wing": meta.get("wing", ""),
|
|
"room": meta.get("room", ""),
|
|
"content_preview": doc[:200] + "..." if len(doc) > 200 else doc,
|
|
}
|
|
)
|
|
return {
|
|
"drawers": drawers,
|
|
"count": len(drawers),
|
|
"offset": offset,
|
|
"limit": limit,
|
|
}
|
|
except Exception as e:
|
|
return {"error": str(e)}
|
|
|
|
|
|
def tool_update_drawer(drawer_id: str, content: str = None, wing: str = None, room: str = None):
|
|
"""Update an existing drawer's content and/or metadata."""
|
|
global _metadata_cache
|
|
|
|
if content is None and wing is None and room is None:
|
|
return {"success": True, "drawer_id": drawer_id, "noop": True}
|
|
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
try:
|
|
existing = col.get(ids=[drawer_id], include=["documents", "metadatas"])
|
|
if not existing["ids"]:
|
|
return {"success": False, "error": f"Drawer not found: {drawer_id}"}
|
|
|
|
old_meta = existing["metadatas"][0]
|
|
old_doc = existing["documents"][0]
|
|
|
|
new_doc = old_doc
|
|
if content is not None:
|
|
try:
|
|
new_doc = sanitize_content(content)
|
|
except ValueError as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
new_meta = dict(old_meta)
|
|
if wing is not None:
|
|
try:
|
|
new_meta["wing"] = sanitize_name(wing, "wing")
|
|
except ValueError as e:
|
|
return {"success": False, "error": str(e)}
|
|
if room is not None:
|
|
try:
|
|
new_meta["room"] = sanitize_name(room, "room")
|
|
except ValueError as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
_wal_log(
|
|
"update_drawer",
|
|
{
|
|
"drawer_id": drawer_id,
|
|
"old_wing": old_meta.get("wing", ""),
|
|
"old_room": old_meta.get("room", ""),
|
|
"new_wing": new_meta.get("wing", ""),
|
|
"new_room": new_meta.get("room", ""),
|
|
"content_changed": content is not None,
|
|
"content_preview": new_doc[:200] if content is not None else None,
|
|
},
|
|
)
|
|
|
|
update_kwargs = {"ids": [drawer_id]}
|
|
if content is not None:
|
|
update_kwargs["documents"] = [new_doc]
|
|
update_kwargs["metadatas"] = [new_meta]
|
|
col.update(**update_kwargs)
|
|
|
|
_metadata_cache = None
|
|
|
|
logger.info(f"Updated drawer: {drawer_id}")
|
|
return {
|
|
"success": True,
|
|
"drawer_id": drawer_id,
|
|
"wing": new_meta.get("wing", ""),
|
|
"room": new_meta.get("room", ""),
|
|
}
|
|
except Exception as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
|
|
# ==================== KNOWLEDGE GRAPH ====================
|
|
|
|
|
|
def tool_kg_query(entity: str, as_of: str = None, direction: str = "both"):
|
|
"""Query the knowledge graph for an entity's relationships."""
|
|
try:
|
|
entity = sanitize_kg_value(entity, "entity")
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
if direction not in ("outgoing", "incoming", "both"):
|
|
return {"error": "direction must be 'outgoing', 'incoming', or 'both'"}
|
|
results = _kg.query_entity(entity, as_of=as_of, direction=direction)
|
|
return {"entity": entity, "as_of": as_of, "facts": results, "count": len(results)}
|
|
|
|
|
|
def tool_kg_add(
|
|
subject: str, predicate: str, object: str, valid_from: str = None, source_closet: str = None
|
|
):
|
|
"""Add a relationship to the knowledge graph."""
|
|
try:
|
|
subject = sanitize_kg_value(subject, "subject")
|
|
predicate = sanitize_name(predicate, "predicate")
|
|
object = sanitize_kg_value(object, "object")
|
|
except ValueError as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
_wal_log(
|
|
"kg_add",
|
|
{
|
|
"subject": subject,
|
|
"predicate": predicate,
|
|
"object": object,
|
|
"valid_from": valid_from,
|
|
"source_closet": source_closet,
|
|
},
|
|
)
|
|
triple_id = _kg.add_triple(
|
|
subject, predicate, object, valid_from=valid_from, source_closet=source_closet
|
|
)
|
|
return {"success": True, "triple_id": triple_id, "fact": f"{subject} → {predicate} → {object}"}
|
|
|
|
|
|
def tool_kg_invalidate(subject: str, predicate: str, object: str, ended: str = None):
|
|
"""Mark a fact as no longer true (set end date)."""
|
|
try:
|
|
subject = sanitize_kg_value(subject, "subject")
|
|
predicate = sanitize_name(predicate, "predicate")
|
|
object = sanitize_kg_value(object, "object")
|
|
except ValueError as e:
|
|
return {"success": False, "error": str(e)}
|
|
_wal_log(
|
|
"kg_invalidate",
|
|
{"subject": subject, "predicate": predicate, "object": object, "ended": ended},
|
|
)
|
|
_kg.invalidate(subject, predicate, object, ended=ended)
|
|
return {
|
|
"success": True,
|
|
"fact": f"{subject} → {predicate} → {object}",
|
|
"ended": ended or "today",
|
|
}
|
|
|
|
|
|
def tool_kg_timeline(entity: str = None):
|
|
"""Get chronological timeline of facts, optionally for one entity."""
|
|
if entity is not None:
|
|
try:
|
|
entity = sanitize_kg_value(entity, "entity")
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
results = _kg.timeline(entity)
|
|
return {"entity": entity or "all", "timeline": results, "count": len(results)}
|
|
|
|
|
|
def tool_kg_stats():
|
|
"""Knowledge graph overview: entities, triples, relationship types."""
|
|
return _kg.stats()
|
|
|
|
|
|
# ==================== AGENT DIARY ====================
|
|
|
|
|
|
def tool_diary_write(agent_name: str, entry: str, topic: str = "general", wing: str = ""):
|
|
"""
|
|
Write a diary entry for this agent. Entries are timestamped and
|
|
accumulate over time in a diary room.
|
|
|
|
This is the agent's personal journal — observations, thoughts,
|
|
what it worked on, what it noticed, what it thinks matters.
|
|
"""
|
|
try:
|
|
agent_name = sanitize_name(agent_name, "agent_name")
|
|
entry = sanitize_content(entry)
|
|
topic = sanitize_name(topic, "topic")
|
|
except ValueError as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
if wing:
|
|
wing = sanitize_name(wing)
|
|
else:
|
|
wing = f"wing_{agent_name.lower().replace(' ', '_')}"
|
|
room = "diary"
|
|
col = _get_collection(create=True)
|
|
if not col:
|
|
return _no_palace()
|
|
|
|
now = datetime.now()
|
|
entry_id = (
|
|
f"diary_{wing}_{now.strftime('%Y%m%d_%H%M%S%f')}_"
|
|
f"{hashlib.sha256(entry.encode()).hexdigest()[:12]}"
|
|
)
|
|
|
|
_wal_log(
|
|
"diary_write",
|
|
{
|
|
"agent_name": agent_name,
|
|
"topic": topic,
|
|
"entry_id": entry_id,
|
|
"entry_preview": entry[:200],
|
|
},
|
|
)
|
|
|
|
try:
|
|
# TODO: Future versions should expand AAAK before embedding to improve
|
|
# semantic search quality. For now, store raw AAAK in metadata so it's
|
|
# preserved, and keep the document as-is for embedding (even though
|
|
# compressed AAAK degrades embedding quality).
|
|
col.add(
|
|
ids=[entry_id],
|
|
documents=[entry],
|
|
metadatas=[
|
|
{
|
|
"wing": wing,
|
|
"room": room,
|
|
"hall": "hall_diary",
|
|
"topic": topic,
|
|
"type": "diary_entry",
|
|
"agent": agent_name,
|
|
"filed_at": now.isoformat(),
|
|
"date": now.strftime("%Y-%m-%d"),
|
|
}
|
|
],
|
|
)
|
|
logger.info(f"Diary entry: {entry_id} → {wing}/diary/{topic}")
|
|
return {
|
|
"success": True,
|
|
"entry_id": entry_id,
|
|
"agent": agent_name,
|
|
"topic": topic,
|
|
"timestamp": now.isoformat(),
|
|
}
|
|
except Exception as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
|
|
def tool_diary_read(agent_name: str, last_n: int = 10, wing: str = ""):
|
|
"""
|
|
Read an agent's recent diary entries. Returns the last N entries
|
|
in chronological order — the agent's personal journal.
|
|
|
|
When ``wing`` is provided, reads only from that wing. When ``wing``
|
|
is empty or omitted, returns entries from every wing this agent has
|
|
written to. Diary writes from hooks land in project-derived wings
|
|
(``wing_<project>``), so requiring a specific wing on read would
|
|
silo those entries from agent-initiated reads.
|
|
"""
|
|
try:
|
|
agent_name = sanitize_name(agent_name, "agent_name")
|
|
if wing:
|
|
wing = sanitize_name(wing)
|
|
except ValueError as e:
|
|
return {"error": str(e)}
|
|
last_n = max(1, min(last_n, 100))
|
|
col = _get_collection()
|
|
if not col:
|
|
return _no_palace()
|
|
|
|
# Build filter: always scope by agent + room=diary. Wing is optional —
|
|
# when empty, return entries across all wings for this agent (matches
|
|
# the #1097 empty-string-as-no-filter convention for LLM ergonomics).
|
|
conditions = [{"room": "diary"}, {"agent": agent_name}]
|
|
if wing:
|
|
conditions.insert(0, {"wing": wing})
|
|
|
|
try:
|
|
results = col.get(
|
|
where={"$and": conditions},
|
|
include=["documents", "metadatas"],
|
|
limit=10000,
|
|
)
|
|
|
|
if not results["ids"]:
|
|
return {"agent": agent_name, "entries": [], "message": "No diary entries yet."}
|
|
|
|
# Combine and sort by timestamp
|
|
entries = []
|
|
for doc, meta in zip(results["documents"], results["metadatas"]):
|
|
entries.append(
|
|
{
|
|
"date": meta.get("date", ""),
|
|
"timestamp": meta.get("filed_at", ""),
|
|
"topic": meta.get("topic", ""),
|
|
"content": doc,
|
|
}
|
|
)
|
|
|
|
entries.sort(key=lambda x: x["timestamp"], reverse=True)
|
|
entries = entries[:last_n]
|
|
|
|
return {
|
|
"agent": agent_name,
|
|
"entries": entries,
|
|
"total": len(results["ids"]),
|
|
"showing": len(entries),
|
|
}
|
|
except Exception:
|
|
logger.exception("diary_read failed")
|
|
return {"error": "Failed to read diary entries"}
|
|
|
|
|
|
def tool_hook_settings(silent_save: bool = None, desktop_toast: bool = None):
|
|
"""
|
|
Get or set hook behavior settings.
|
|
|
|
- silent_save: True = stop hook saves directly (no MCP clutter),
|
|
False = legacy blocking MCP calls. Default: True.
|
|
- desktop_toast: True = show notify-send desktop toast on save,
|
|
False = terminal-only notification. Default: False.
|
|
|
|
Call with no arguments to see current settings.
|
|
"""
|
|
from .config import MempalaceConfig
|
|
|
|
try:
|
|
config = MempalaceConfig()
|
|
except Exception as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
changed = []
|
|
if silent_save is not None:
|
|
config.set_hook_setting("silent_save", silent_save)
|
|
changed.append(f"silent_save → {silent_save}")
|
|
if desktop_toast is not None:
|
|
config.set_hook_setting("desktop_toast", desktop_toast)
|
|
changed.append(f"desktop_toast → {desktop_toast}")
|
|
|
|
# Re-read to return current state
|
|
try:
|
|
config = MempalaceConfig()
|
|
except Exception:
|
|
pass
|
|
|
|
result = {
|
|
"success": True,
|
|
"settings": {
|
|
"silent_save": config.hook_silent_save,
|
|
"desktop_toast": config.hook_desktop_toast,
|
|
},
|
|
}
|
|
if changed:
|
|
result["updated"] = changed
|
|
return result
|
|
|
|
|
|
def tool_memories_filed_away():
|
|
"""Acknowledge the latest silent checkpoint. Returns a short summary."""
|
|
state_dir = Path.home() / ".mempalace" / "hook_state"
|
|
ack_file = state_dir / "last_checkpoint"
|
|
if not ack_file.is_file():
|
|
return {
|
|
"status": "quiet",
|
|
"message": "No recent journal entry",
|
|
"count": 0,
|
|
"timestamp": None,
|
|
}
|
|
try:
|
|
data = json.loads(ack_file.read_text(encoding="utf-8"))
|
|
ack_file.unlink(missing_ok=True)
|
|
msgs = data.get("msgs", 0)
|
|
return {
|
|
"status": "ok",
|
|
"message": f"\u2726 {msgs} messages tucked into drawers",
|
|
"count": msgs,
|
|
"timestamp": data.get("ts", None),
|
|
}
|
|
except (json.JSONDecodeError, OSError):
|
|
ack_file.unlink(missing_ok=True)
|
|
return {
|
|
"status": "error",
|
|
"message": "\u2726 Journal entry filed in the palace",
|
|
"count": 0,
|
|
"timestamp": None,
|
|
}
|
|
|
|
|
|
# ==================== SETTINGS TOOLS ====================
|
|
|
|
|
|
def tool_reconnect():
|
|
"""Force the MCP server to drop the cached ChromaDB collection and reconnect.
|
|
|
|
Use after external scripts or CLI commands modify the palace database
|
|
directly, which can leave the in-memory HNSW index stale.
|
|
"""
|
|
global \
|
|
_client_cache, \
|
|
_collection_cache, \
|
|
_palace_db_inode, \
|
|
_palace_db_mtime, \
|
|
_vector_disabled, \
|
|
_vector_disabled_reason
|
|
_client_cache = None
|
|
_collection_cache = None
|
|
_palace_db_inode = 0
|
|
_palace_db_mtime = 0.0
|
|
# Force probe re-run on next _get_client by clearing the flag now;
|
|
# _refresh_vector_disabled_flag will re-set it if the divergence
|
|
# still applies after the reconnect.
|
|
_vector_disabled = False
|
|
_vector_disabled_reason = ""
|
|
try:
|
|
col = _get_collection()
|
|
if col is None:
|
|
return {
|
|
"success": False,
|
|
"message": "No palace found after reconnect",
|
|
"drawers": 0,
|
|
"vector_disabled": _vector_disabled,
|
|
}
|
|
return {
|
|
"success": True,
|
|
"message": "Reconnected to palace",
|
|
"drawers": col.count(),
|
|
"vector_disabled": _vector_disabled,
|
|
"vector_disabled_reason": _vector_disabled_reason,
|
|
}
|
|
except Exception as e:
|
|
return {"success": False, "error": str(e)}
|
|
|
|
|
|
# ==================== MCP PROTOCOL ====================
|
|
|
|
TOOLS = {
|
|
"mempalace_status": {
|
|
"description": "Palace overview — total drawers, wing and room counts",
|
|
"input_schema": {"type": "object", "properties": {}},
|
|
"handler": tool_status,
|
|
},
|
|
"mempalace_list_wings": {
|
|
"description": "List all wings with drawer counts",
|
|
"input_schema": {"type": "object", "properties": {}},
|
|
"handler": tool_list_wings,
|
|
},
|
|
"mempalace_list_rooms": {
|
|
"description": "List rooms within a wing (or all rooms if no wing given)",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"wing": {"type": "string", "description": "Wing to list rooms for (optional)"},
|
|
},
|
|
},
|
|
"handler": tool_list_rooms,
|
|
},
|
|
"mempalace_get_taxonomy": {
|
|
"description": "Full taxonomy: wing → room → drawer count",
|
|
"input_schema": {"type": "object", "properties": {}},
|
|
"handler": tool_get_taxonomy,
|
|
},
|
|
"mempalace_get_aaak_spec": {
|
|
"description": "Get the AAAK dialect specification — the compressed memory format MemPalace uses. Call this if you need to read or write AAAK-compressed memories.",
|
|
"input_schema": {"type": "object", "properties": {}},
|
|
"handler": tool_get_aaak_spec,
|
|
},
|
|
"mempalace_kg_query": {
|
|
"description": "Query the knowledge graph for an entity's relationships. Returns typed facts with temporal validity. E.g. 'Max' → child_of Alice, loves chess, does swimming. Filter by date with as_of to see what was true at a point in time.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"entity": {
|
|
"type": "string",
|
|
"description": "Entity to query (e.g. 'Max', 'MyProject', 'Alice')",
|
|
},
|
|
"as_of": {
|
|
"type": "string",
|
|
"description": "Date filter — only facts valid at this date (YYYY-MM-DD, optional)",
|
|
},
|
|
"direction": {
|
|
"type": "string",
|
|
"description": "outgoing (entity→?), incoming (?→entity), or both (default: both)",
|
|
},
|
|
},
|
|
"required": ["entity"],
|
|
},
|
|
"handler": tool_kg_query,
|
|
},
|
|
"mempalace_kg_add": {
|
|
"description": "Add a fact to the knowledge graph. Subject → predicate → object with optional time window. E.g. ('Max', 'started_school', 'Year 7', valid_from='2026-09-01').",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"subject": {"type": "string", "description": "The entity doing/being something"},
|
|
"predicate": {
|
|
"type": "string",
|
|
"description": "The relationship type (e.g. 'loves', 'works_on', 'daughter_of')",
|
|
},
|
|
"object": {"type": "string", "description": "The entity being connected to"},
|
|
"valid_from": {
|
|
"type": "string",
|
|
"description": "When this became true (YYYY-MM-DD, optional)",
|
|
},
|
|
"source_closet": {
|
|
"type": "string",
|
|
"description": "Closet ID where this fact appears (optional)",
|
|
},
|
|
},
|
|
"required": ["subject", "predicate", "object"],
|
|
},
|
|
"handler": tool_kg_add,
|
|
},
|
|
"mempalace_kg_invalidate": {
|
|
"description": "Mark a fact as no longer true. E.g. ankle injury resolved, job ended, moved house.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"subject": {"type": "string", "description": "Entity"},
|
|
"predicate": {"type": "string", "description": "Relationship"},
|
|
"object": {"type": "string", "description": "Connected entity"},
|
|
"ended": {
|
|
"type": "string",
|
|
"description": "When it stopped being true (YYYY-MM-DD, default: today)",
|
|
},
|
|
},
|
|
"required": ["subject", "predicate", "object"],
|
|
},
|
|
"handler": tool_kg_invalidate,
|
|
},
|
|
"mempalace_kg_timeline": {
|
|
"description": "Chronological timeline of facts. Shows the story of an entity (or everything) in order.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"entity": {
|
|
"type": "string",
|
|
"description": "Entity to get timeline for (optional — omit for full timeline)",
|
|
},
|
|
},
|
|
},
|
|
"handler": tool_kg_timeline,
|
|
},
|
|
"mempalace_kg_stats": {
|
|
"description": "Knowledge graph overview: entities, triples, current vs expired facts, relationship types.",
|
|
"input_schema": {"type": "object", "properties": {}},
|
|
"handler": tool_kg_stats,
|
|
},
|
|
"mempalace_traverse": {
|
|
"description": "Walk the palace graph from a room. Shows connected ideas across wings — the tunnels. Like following a thread through the palace: start at 'chromadb-setup' in wing_code, discover it connects to wing_myproject (planning) and wing_user (feelings about it).",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"start_room": {
|
|
"type": "string",
|
|
"description": "Room to start from (e.g. 'chromadb-setup', 'riley-school')",
|
|
},
|
|
"max_hops": {
|
|
"type": "integer",
|
|
"description": "How many connections to follow (default: 2)",
|
|
},
|
|
},
|
|
"required": ["start_room"],
|
|
},
|
|
"handler": tool_traverse_graph,
|
|
},
|
|
"mempalace_find_tunnels": {
|
|
"description": "Find rooms that bridge two wings — the hallways connecting different domains. E.g. what topics connect wing_code to wing_team?",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"wing_a": {"type": "string", "description": "First wing (optional)"},
|
|
"wing_b": {"type": "string", "description": "Second wing (optional)"},
|
|
},
|
|
},
|
|
"handler": tool_find_tunnels,
|
|
},
|
|
"mempalace_graph_stats": {
|
|
"description": "Palace graph overview: total rooms, tunnel connections, edges between wings.",
|
|
"input_schema": {"type": "object", "properties": {}},
|
|
"handler": tool_graph_stats,
|
|
},
|
|
"mempalace_create_tunnel": {
|
|
"description": "Create a cross-wing tunnel linking two palace locations. Use when content in one project relates to another — e.g., an API design in project_api connects to a database schema in project_database.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"source_wing": {"type": "string", "description": "Wing of the source"},
|
|
"source_room": {"type": "string", "description": "Room in the source wing"},
|
|
"target_wing": {"type": "string", "description": "Wing of the target"},
|
|
"target_room": {"type": "string", "description": "Room in the target wing"},
|
|
"label": {"type": "string", "description": "Description of the connection"},
|
|
"source_drawer_id": {
|
|
"type": "string",
|
|
"description": "Optional specific drawer ID",
|
|
},
|
|
"target_drawer_id": {
|
|
"type": "string",
|
|
"description": "Optional specific drawer ID",
|
|
},
|
|
},
|
|
"required": ["source_wing", "source_room", "target_wing", "target_room"],
|
|
},
|
|
"handler": tool_create_tunnel,
|
|
},
|
|
"mempalace_list_tunnels": {
|
|
"description": "List all explicit cross-wing tunnels. Optionally filter by wing.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"wing": {
|
|
"type": "string",
|
|
"description": "Filter tunnels by wing (shows tunnels where wing is source or target)",
|
|
},
|
|
},
|
|
},
|
|
"handler": tool_list_tunnels,
|
|
},
|
|
"mempalace_delete_tunnel": {
|
|
"description": "Delete an explicit tunnel by its ID.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"tunnel_id": {"type": "string", "description": "Tunnel ID to delete"},
|
|
},
|
|
"required": ["tunnel_id"],
|
|
},
|
|
"handler": tool_delete_tunnel,
|
|
},
|
|
"mempalace_follow_tunnels": {
|
|
"description": "Follow tunnels from a room to see what it connects to in other wings. Returns connected rooms with drawer previews.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"wing": {"type": "string", "description": "Wing to start from"},
|
|
"room": {"type": "string", "description": "Room to follow tunnels from"},
|
|
},
|
|
"required": ["wing", "room"],
|
|
},
|
|
"handler": tool_follow_tunnels,
|
|
},
|
|
"mempalace_search": {
|
|
"description": "Semantic search. Returns verbatim drawer content with similarity scores. IMPORTANT: 'query' must contain ONLY search keywords. Use 'context' for background. Results with cosine distance > max_distance are filtered out.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"query": {
|
|
"type": "string",
|
|
"description": "Short search query ONLY — keywords or a question. Max 250 chars.",
|
|
"maxLength": 250,
|
|
},
|
|
"limit": {
|
|
"type": "integer",
|
|
"description": "Max results (default 5)",
|
|
"minimum": 1,
|
|
"maximum": 100,
|
|
},
|
|
"wing": {"type": "string", "description": "Filter by wing (optional)"},
|
|
"room": {"type": "string", "description": "Filter by room (optional)"},
|
|
"max_distance": {
|
|
"type": "number",
|
|
"description": "Max cosine distance threshold (0=identical, 2=opposite). Results further than this are dropped. Lower = stricter. Default 1.5. Set to 0 to disable.",
|
|
},
|
|
"context": {
|
|
"type": "string",
|
|
"description": "Background context for the search (optional). NOT used for embedding — only for future re-ranking.",
|
|
},
|
|
},
|
|
"required": ["query"],
|
|
},
|
|
"handler": tool_search,
|
|
},
|
|
"mempalace_check_duplicate": {
|
|
"description": "Check if content already exists in the palace before filing",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"content": {"type": "string", "description": "Content to check"},
|
|
"threshold": {
|
|
"type": "number",
|
|
"description": "Similarity threshold 0-1 (default 0.9)",
|
|
},
|
|
},
|
|
"required": ["content"],
|
|
},
|
|
"handler": tool_check_duplicate,
|
|
},
|
|
"mempalace_add_drawer": {
|
|
"description": "File verbatim content into the palace. Checks for duplicates first.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"wing": {"type": "string", "description": "Wing (project name)"},
|
|
"room": {
|
|
"type": "string",
|
|
"description": "Room (aspect: backend, decisions, meetings...)",
|
|
},
|
|
"content": {
|
|
"type": "string",
|
|
"description": "Verbatim content to store — exact words, never summarized",
|
|
},
|
|
"source_file": {"type": "string", "description": "Where this came from (optional)"},
|
|
"added_by": {"type": "string", "description": "Who is filing this (default: mcp)"},
|
|
},
|
|
"required": ["wing", "room", "content"],
|
|
},
|
|
"handler": tool_add_drawer,
|
|
},
|
|
"mempalace_delete_drawer": {
|
|
"description": "Delete a drawer by ID. Irreversible.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"drawer_id": {"type": "string", "description": "ID of the drawer to delete"},
|
|
},
|
|
"required": ["drawer_id"],
|
|
},
|
|
"handler": tool_delete_drawer,
|
|
},
|
|
"mempalace_get_drawer": {
|
|
"description": "Fetch a single drawer by ID — returns full content and metadata.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"drawer_id": {"type": "string", "description": "ID of the drawer to fetch"},
|
|
},
|
|
"required": ["drawer_id"],
|
|
},
|
|
"handler": tool_get_drawer,
|
|
},
|
|
"mempalace_list_drawers": {
|
|
"description": "List drawers with pagination. Optional wing/room filter. Returns IDs, wings, rooms, and content previews.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"wing": {"type": "string", "description": "Filter by wing (optional)"},
|
|
"room": {"type": "string", "description": "Filter by room (optional)"},
|
|
"limit": {
|
|
"type": "integer",
|
|
"description": "Max results per page (default 20, max 100)",
|
|
"minimum": 1,
|
|
"maximum": 100,
|
|
},
|
|
"offset": {
|
|
"type": "integer",
|
|
"description": "Offset for pagination (default 0)",
|
|
"minimum": 0,
|
|
},
|
|
},
|
|
},
|
|
"handler": tool_list_drawers,
|
|
},
|
|
"mempalace_update_drawer": {
|
|
"description": "Update an existing drawer's content and/or metadata (wing, room). Fetches existing drawer first; returns error if not found.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"drawer_id": {"type": "string", "description": "ID of the drawer to update"},
|
|
"content": {
|
|
"type": "string",
|
|
"description": "New content (optional — omit to keep existing)",
|
|
},
|
|
"wing": {
|
|
"type": "string",
|
|
"description": "New wing (optional — omit to keep existing)",
|
|
},
|
|
"room": {
|
|
"type": "string",
|
|
"description": "New room (optional — omit to keep existing)",
|
|
},
|
|
},
|
|
"required": ["drawer_id"],
|
|
},
|
|
"handler": tool_update_drawer,
|
|
},
|
|
"mempalace_diary_write": {
|
|
"description": "Write to your personal agent diary in AAAK format. Your observations, thoughts, what you worked on, what matters. Each agent has their own diary with full history. Write in AAAK for compression — e.g. 'SESSION:2026-04-04|built.palace.graph+diary.tools|ALC.req:agent.diaries.in.aaak|★★★'. Use entity codes from the AAAK spec.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"agent_name": {
|
|
"type": "string",
|
|
"description": "Your name — each agent gets their own diary wing",
|
|
},
|
|
"entry": {
|
|
"type": "string",
|
|
"description": "Your diary entry in AAAK format — compressed, entity-coded, emotion-marked",
|
|
},
|
|
"topic": {
|
|
"type": "string",
|
|
"description": "Topic tag (optional, default: general)",
|
|
},
|
|
"wing": {
|
|
"type": "string",
|
|
"description": "Target wing for this diary entry (optional). If omitted, uses wing_{agent_name}. Use this to write diary entries to a project wing instead of an agent-specific wing.",
|
|
},
|
|
},
|
|
"required": ["agent_name", "entry"],
|
|
},
|
|
"handler": tool_diary_write,
|
|
},
|
|
"mempalace_diary_read": {
|
|
"description": "Read your recent diary entries (in AAAK). See what past versions of yourself recorded — your journal across sessions.",
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"agent_name": {
|
|
"type": "string",
|
|
"description": "Your name — each agent gets their own diary wing",
|
|
},
|
|
"last_n": {
|
|
"type": "integer",
|
|
"description": "Number of recent entries to read (default: 10)",
|
|
},
|
|
"wing": {
|
|
"type": "string",
|
|
"description": "Wing to read diary entries from (optional). If omitted, reads from wing_{agent_name}.",
|
|
},
|
|
},
|
|
"required": ["agent_name"],
|
|
},
|
|
"handler": tool_diary_read,
|
|
},
|
|
"mempalace_hook_settings": {
|
|
"description": (
|
|
"Get or set hook behavior. silent_save: True = save directly "
|
|
"(no MCP clutter), False = legacy blocking. desktop_toast: "
|
|
"True = show desktop notification. Call with no args to view."
|
|
),
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {
|
|
"silent_save": {
|
|
"type": "boolean",
|
|
"description": "True = silent direct save, False = blocking MCP calls",
|
|
},
|
|
"desktop_toast": {
|
|
"type": "boolean",
|
|
"description": "True = show desktop toast via notify-send",
|
|
},
|
|
},
|
|
},
|
|
"handler": tool_hook_settings,
|
|
},
|
|
"mempalace_memories_filed_away": {
|
|
"description": "Check if a recent palace checkpoint was saved. Returns message count and timestamp.",
|
|
"input_schema": {"type": "object", "properties": {}},
|
|
"handler": tool_memories_filed_away,
|
|
},
|
|
"mempalace_reconnect": {
|
|
"description": (
|
|
"Force reconnect to the palace database. Use after external scripts or CLI commands"
|
|
" modified the palace directly, which can leave the in-memory HNSW index stale."
|
|
),
|
|
"input_schema": {
|
|
"type": "object",
|
|
"properties": {},
|
|
},
|
|
"handler": tool_reconnect,
|
|
},
|
|
}
|
|
|
|
|
|
SUPPORTED_PROTOCOL_VERSIONS = [
|
|
"2025-11-25",
|
|
"2025-06-18",
|
|
"2025-03-26",
|
|
"2024-11-05",
|
|
]
|
|
|
|
|
|
def handle_request(request):
|
|
method = request.get("method") or ""
|
|
params = request.get("params") or {}
|
|
req_id = request.get("id")
|
|
|
|
if method == "initialize":
|
|
client_version = params.get("protocolVersion", SUPPORTED_PROTOCOL_VERSIONS[-1])
|
|
negotiated = (
|
|
client_version
|
|
if client_version in SUPPORTED_PROTOCOL_VERSIONS
|
|
else SUPPORTED_PROTOCOL_VERSIONS[0]
|
|
)
|
|
return {
|
|
"jsonrpc": "2.0",
|
|
"id": req_id,
|
|
"result": {
|
|
"protocolVersion": negotiated,
|
|
"capabilities": {"tools": {}},
|
|
"serverInfo": {"name": "mempalace", "version": __version__},
|
|
},
|
|
}
|
|
elif method == "ping":
|
|
return {"jsonrpc": "2.0", "id": req_id, "result": {}}
|
|
elif method.startswith("notifications/"):
|
|
# Notifications (no id) never get a response per JSON-RPC spec
|
|
return None
|
|
elif method == "tools/list":
|
|
return {
|
|
"jsonrpc": "2.0",
|
|
"id": req_id,
|
|
"result": {
|
|
"tools": [
|
|
{"name": n, "description": t["description"], "inputSchema": t["input_schema"]}
|
|
for n, t in TOOLS.items()
|
|
]
|
|
},
|
|
}
|
|
elif method == "tools/call":
|
|
tool_name = params.get("name")
|
|
tool_args = params.get("arguments") or {}
|
|
if tool_name not in TOOLS:
|
|
return {
|
|
"jsonrpc": "2.0",
|
|
"id": req_id,
|
|
"error": {"code": -32601, "message": f"Unknown tool: {tool_name}"},
|
|
}
|
|
# Whitelist arguments to declared schema properties only.
|
|
# Prevents callers from spoofing internal params like added_by/source_file.
|
|
# Skip filtering if handler explicitly accepts **kwargs (pass-through).
|
|
# Default to filtering on inspect failure (safe fallback).
|
|
import inspect
|
|
|
|
schema_props = TOOLS[tool_name]["input_schema"].get("properties", {})
|
|
try:
|
|
handler = TOOLS[tool_name]["handler"]
|
|
sig = inspect.signature(handler)
|
|
accepts_var_keyword = any(
|
|
p.kind == inspect.Parameter.VAR_KEYWORD for p in sig.parameters.values()
|
|
)
|
|
except (ValueError, TypeError):
|
|
accepts_var_keyword = False
|
|
if not accepts_var_keyword:
|
|
tool_args = {k: v for k, v in tool_args.items() if k in schema_props}
|
|
# Coerce argument types based on input_schema.
|
|
# MCP JSON transport may deliver integers as floats or strings;
|
|
# ChromaDB and Python slicing require native int.
|
|
for key, value in list(tool_args.items()):
|
|
prop_schema = schema_props.get(key, {})
|
|
declared_type = prop_schema.get("type")
|
|
try:
|
|
if declared_type == "integer" and not isinstance(value, int):
|
|
tool_args[key] = int(value)
|
|
elif declared_type == "number" and not isinstance(value, (int, float)):
|
|
tool_args[key] = float(value)
|
|
except (ValueError, TypeError):
|
|
return {
|
|
"jsonrpc": "2.0",
|
|
"id": req_id,
|
|
"error": {"code": -32602, "message": f"Invalid value for parameter '{key}'"},
|
|
}
|
|
try:
|
|
tool_args.pop("wait_for_previous", None)
|
|
result = TOOLS[tool_name]["handler"](**tool_args)
|
|
return {
|
|
"jsonrpc": "2.0",
|
|
"id": req_id,
|
|
"result": {"content": [{"type": "text", "text": json.dumps(result, indent=2)}]},
|
|
}
|
|
except Exception:
|
|
logger.exception(f"Tool error in {tool_name}")
|
|
return {
|
|
"jsonrpc": "2.0",
|
|
"id": req_id,
|
|
"error": {"code": -32000, "message": "Internal tool error"},
|
|
}
|
|
|
|
# Notifications (missing id) must never get a response
|
|
if req_id is None:
|
|
return None
|
|
return {
|
|
"jsonrpc": "2.0",
|
|
"id": req_id,
|
|
"error": {"code": -32601, "message": f"Unknown method: {method}"},
|
|
}
|
|
|
|
|
|
def _restore_stdout():
|
|
"""Restore real stdout for MCP JSON-RPC output (see issue #225)."""
|
|
global _REAL_STDOUT, _REAL_STDOUT_FD
|
|
if _REAL_STDOUT_FD is not None:
|
|
try:
|
|
os.dup2(_REAL_STDOUT_FD, 1)
|
|
os.close(_REAL_STDOUT_FD)
|
|
except OSError:
|
|
pass
|
|
_REAL_STDOUT_FD = None
|
|
sys.stdout = _REAL_STDOUT
|
|
|
|
|
|
def main():
|
|
_restore_stdout()
|
|
logger.info("MemPalace MCP Server starting...")
|
|
# Pre-flight: probe HNSW capacity before any tool call so the warning
|
|
# is visible at startup rather than on first use (#1222). Pure
|
|
# filesystem read; never opens a chromadb client.
|
|
_refresh_vector_disabled_flag()
|
|
while True:
|
|
try:
|
|
line = sys.stdin.readline()
|
|
if not line:
|
|
break
|
|
line = line.strip()
|
|
if not line:
|
|
continue
|
|
request = json.loads(line)
|
|
response = handle_request(request)
|
|
if response is not None:
|
|
sys.stdout.write(json.dumps(response) + "\n")
|
|
sys.stdout.flush()
|
|
except KeyboardInterrupt:
|
|
break
|
|
except Exception as e:
|
|
logger.error(f"Server error: {e}")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|