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Second Brain MCP

Second Brain MCP

by PandaTBE

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      Enables AI agents and MCP hosts to search and ask questions across a local hybrid-retrieval index of scattered notes, documents, PDFs, and chat logs, returning section-level citations and agent-usable tools, resources, and prompts.
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      Enables AI agents to query your complete local conversation history and knowledge graph over MCP, including full-fidelity transcripts, search, and typed, dated entity relationships.
      AGPL 3.0

    TDQS

    A3.7/5.0

    Scored across 7 tools

    Disambiguation4/5

    The set forms a readable retrieval pipeline: search_memory finds snippets, get_record fetches a record by search ID, get_evidence_bundle returns exact quotes with citation IDs, and get_facts/get_fact_history/get_context_brief cover derived views. The closest overlap is search_memory vs get_evidence_bundle, which both rank BM25/embedding results with similar filters and differ mainly in output shape (scores vs exact quotes). Descriptions do disambiguate, so an attentive agent can pick correctly, but the boundary takes reading.

    Naming Consistency5/5

    All names are snake_case verb_noun pairs: six get_* accessors plus search_memory. The single search_ verb is a meaningful, not arbitrary, deviation since that tool ranks rather than fetches by identity.

    Tool Count5/5

    Seven tools is well within the sweet spot and each has a distinct role in the read path (search, record, evidence, facts, history, brief, status). Nothing appears redundant or padding.

    Completeness4/5

    The read surface is thorough: discovery, ID-based fetch, evidence with citations, current facts, revision history, briefings, and sync health are all covered. The obvious gap is the write side — no tool creates or updates memories — though the descriptions frame this as deliberate (imports and paid inference happen outside MCP), and there is no browse/list-by-project tool for exploration.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues