recall-mcp
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- AlicenseNot gradedqualityBmaintenanceEnables Claude Code to search and retrieve from a local knowledge base of markdown notes using hybrid semantic+keyword search, keeping data entirely offline.10 npmMIT
- AlicenseNot gradedqualityCmaintenanceTurns any folder of Markdown files into a searchable, structured knowledge base for Claude Code, enabling persistent memory across sessions via tools like list, read, write, edit, search, and summarize.MIT
- AlicenseNot gradedqualityDmaintenanceEnables Claude to perform hybrid search across local documents by combining semantic vector retrieval and BM25 keyword matching for optimal context recovery. It supports multiple file formats including PDF, CSV, and Markdown, leveraging local Ollama models for private and efficient document querying.4MIT
- AlicenseNot gradedqualityDmaintenanceEnables hybrid vector-BM25 search and retrieval of Obsidian vault knowledge notes, allowing AI assistants like Claude to efficiently access relevant chunks without full file reads.MIT
- AlicenseAqualityBmaintenanceEnables semantic search and reading of Obsidian Markdown notes through read-only MCP tools, allowing Claude to retrieve relevant passages from a local vault.3MIT
- AlicenseNot gradedqualityDmaintenancePersistent session memory for Claude Code, providing episodic recall across sessions via structured markdown logs and BM25 search.1MIT
TDQS
Scored across 1 tool
With only one exposed tool, there is no inter-tool ambiguity. The internal actions—search, latest, thread, verify, import, capture, get, neighbors, index—are each clearly separated by purpose, so an agent can reliably select among them. This is trivially unambiguous as a tool set.
The single tool name 'memory' is a generic noun rather than a clear verb_noun or action-oriented name, and it provides no observable naming pattern. Internally, action names mix styles such as 'latest' and 'search' with 'index_status' and 'probe_status', so consistency is only fair.
One tool for a rich recall domain is too few; all functionality is crammed into a single monolithic memory command with many sub-actions. This makes the surface look thinner than it is and forces agents to parse a massive description. A small set of focused tools would be more appropriate for the scope.
The tool covers search, chronological state queries, thread following, git verification, import, capture, indexing, tier management, library scoping, and staleness detection—a comprehensive memory lifecycle. It even anticipates failure modes like stale indexes and async rebuilds. No obvious retrieval or state-checking gap remains.