* feat: MCP reliability — inode detection, WAL rotation, metadata cache, search limits Infrastructure hardening for the MCP server: - Detect palace DB replacement via inode tracking (repair command support) - WAL rotation to prevent unbounded WAL growth - _fetch_all_metadata() + _get_cached_metadata() with 60s TTL for taxonomy/status - _MAX_RESULTS cap (100) with limit clamping [1, _MAX_RESULTS] - max_distance parameter for similarity threshold in search - Handle all notifications/* methods, null arguments, method=None - Remove duplicate _client_cache = None declarations - searcher.py max_distance parameter passthrough Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: new MCP tools (get/list/update drawer, hook settings, memories filed), export, normalize New MCP tools: - mempalace_get_drawer: fetch single drawer by ID with full content - mempalace_list_drawers: paginated listing with wing/room filter - mempalace_update_drawer: update content/wing/room on existing drawers - mempalace_hook_settings: get/set hook behavior (silent_save, desktop_toast) - mempalace_memories_filed_away: check latest checkpoint status Also includes: - exporter.py: export palace as browsable markdown files - normalize.py: tool_use/tool_result capture for richer transcript mining - layers.py: updated for new tool integration - config.py: hook settings properties (hook_silent_save, hook_desktop_toast) Depends on PR 3 (reliability) for _MAX_RESULTS, _metadata_cache, WAL logging. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: normalize.py handles string messages and Read offset type mismatch Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: params null guard, L2→cosine docs, empty tool_use_map key guard - Handle explicit null in MCP params (request.get("params") or {}) - Fix search tool description: L2 → cosine distance (collection uses hnsw:space=cosine) - Guard against empty string key in tool_use_map from malformed JSONL entries Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: rename ambiguous var 'l' to 'line' (E741 lint) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: address code review findings (5 issues) 1. min_similarity backwards-compat: convert similarity to distance scale (1.0 - similarity) instead of passing raw value as max_distance 2. Restore structured error reporting (error + partial fields) in tool_status, tool_list_wings, tool_list_rooms, tool_get_taxonomy — reverts silent except:pass that dropped #647 security hardening 3. inode cache: remove falsy-zero short-circuit so missing DB file triggers reconnect instead of reusing stale client 4. _fetch_all_metadata: check for empty batch before extending/advancing offset to prevent infinite loop on concurrent deletion 5. KG initialization: only override path when --palace is explicit; default runs use KnowledgeGraph's built-in default path Co-authored-by: jphein <jphein@users.noreply.github.com> --------- Co-authored-by: jp <jp@jphein.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: jphein <jphein@users.noreply.github.com>
This commit is contained in:
Ben Sigman
+39
-21
@@ -18,6 +18,17 @@ class SearchError(Exception):
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"""Raised when search cannot proceed (e.g. no palace found)."""
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def build_where_filter(wing: str = None, room: str = None) -> dict:
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"""Build ChromaDB where filter for wing/room filtering."""
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if wing and room:
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return {"$and": [{"wing": wing}, {"room": room}]}
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elif wing:
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return {"wing": wing}
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elif room:
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return {"room": room}
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return {}
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def search(query: str, palace_path: str, wing: str = None, room: str = None, n_results: int = 5):
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"""
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Search the palace. Returns verbatim drawer content.
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@@ -30,14 +41,7 @@ def search(query: str, palace_path: str, wing: str = None, room: str = None, n_r
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print(" Run: mempalace init <dir> then mempalace mine <dir>")
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raise SearchError(f"No palace found at {palace_path}")
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# Build where filter
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where = {}
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if wing and room:
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where = {"$and": [{"wing": wing}, {"room": room}]}
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elif wing:
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where = {"wing": wing}
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elif room:
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where = {"room": room}
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where = build_where_filter(wing, room)
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try:
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kwargs = {
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@@ -71,7 +75,7 @@ def search(query: str, palace_path: str, wing: str = None, room: str = None, n_r
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print(f"{'=' * 60}\n")
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for i, (doc, meta, dist) in enumerate(zip(docs, metas, dists), 1):
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similarity = round(1 - dist, 3)
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similarity = round(max(0.0, 1 - dist), 3)
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source = Path(meta.get("source_file", "?")).name
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wing_name = meta.get("wing", "?")
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room_name = meta.get("room", "?")
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@@ -90,11 +94,27 @@ def search(query: str, palace_path: str, wing: str = None, room: str = None, n_r
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def search_memories(
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query: str, palace_path: str, wing: str = None, room: str = None, n_results: int = 5
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query: str,
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palace_path: str,
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wing: str = None,
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room: str = None,
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n_results: int = 5,
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max_distance: float = 0.0,
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) -> dict:
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"""
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Programmatic search — returns a dict instead of printing.
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"""Programmatic search — returns a dict instead of printing.
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Used by the MCP server and other callers that need data.
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Args:
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query: Natural language search query.
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palace_path: Path to the ChromaDB palace directory.
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wing: Optional wing filter.
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room: Optional room filter.
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n_results: Max results to return.
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max_distance: Max cosine distance threshold. The palace collection uses
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cosine distance (hnsw:space=cosine) — 0 = identical, 2 = opposite.
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Results with distance > this value are filtered out. A value of
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0.0 disables filtering. Typical useful range: 0.3–1.0.
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"""
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try:
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col = get_collection(palace_path, create=False)
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@@ -105,14 +125,7 @@ def search_memories(
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"hint": "Run: mempalace init <dir> && mempalace mine <dir>",
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}
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# Build where filter
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where = {}
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if wing and room:
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where = {"$and": [{"wing": wing}, {"room": room}]}
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elif wing:
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where = {"wing": wing}
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elif room:
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where = {"room": room}
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where = build_where_filter(wing, room)
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try:
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kwargs = {
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@@ -133,18 +146,23 @@ def search_memories(
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hits = []
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for doc, meta, dist in zip(docs, metas, dists):
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# Filter on raw distance before rounding to avoid precision loss
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if max_distance > 0.0 and dist > max_distance:
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continue
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hits.append(
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{
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"text": doc,
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"wing": meta.get("wing", "unknown"),
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"room": meta.get("room", "unknown"),
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"source_file": Path(meta.get("source_file", "?")).name,
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"similarity": round(1 - dist, 3),
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"similarity": round(max(0.0, 1 - dist), 3),
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"distance": round(dist, 4),
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}
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)
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return {
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"query": query,
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"filters": {"wing": wing, "room": room},
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"total_before_filter": len(docs),
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"results": hits,
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}
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