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    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding agents to maintain persistent memory across repositories by indexing local files into a semantic graph and providing ranked, verified search results without LLM token costs.
      3 npm
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    • A
      license
      A
      quality
      B
      maintenance
      Self-hosted semantic code search for AI coding agents. Indexes many repositories at once with tree-sitter AST chunking, local llama.cpp embeddings and Qdrant, so Claude Code, Cursor, Codex and any MCP client can find code by meaning, trace usages and callers, and read the git history behind each chunk. No API keys, and your code never leaves your machine.
      2
      18
      11
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Gives multiple AI coding agents a shared, persistent memory by indexing your code and documentation into a vector database with AST-aware chunking and hybrid semantic/keyword search. Agents can search across projects and store, update, or forget decisions, conventions and lessons learned, all self-hosted with local embeddings.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents to query a local semantic code graph for surgical context, cross-file resolution, framework-aware routes, and code intelligence while keeping indexes automatically up to date.
      77,341 npm
      MIT
    • F
      license
      Not graded
      quality
      C
      maintenance
      Enables AI coding tools to query a local index of documents, code, and crawled web pages using hybrid keyword and semantic search with re-ranking, plus knowledge graph, memory, and agent workflow tools. It also lets clients trigger source syncing and ingestion so context stays current.
      -

    TDQS

    B3/5.0

    Scored across 9 tools

    Disambiguation4/5

    Most tools have distinct purposes (impact=change effects, path=relationship route, why=ranking explanation, feedback=telemetry), but there is mild overlap between mimry_preflight and mimry_status (both readiness/state checks) and between mimry_find and mimry_related (both return files for a query). The descriptions largely disambiguate these, but an agent could still hesitate on which readiness or file-retrieval call to pick.

    Naming Consistency4/5

    All tools share a uniform mimry_ prefix and single lowercase word style, which is predictable and readable. However the words mix nouns (impact, path, status, symbol) and verbs (find, why, feedback), so it is consistent in form but not a strict verb_noun pattern.

    Tool Count5/5

    Nine tools is well-scoped for a code-graph/search server, with each tool covering a distinct facet (search, symbols, relationships, impact, status, feedback). No filler or redundant entries.

    Completeness4/5

    The surface covers search, symbol lookup, graph relationships, change impact, ranking explanation, and readiness/freshness well. The one notable gap is a dedicated index build/reindex operation, since status/preflight only report freshness rather than triggering indexing.

    Maintenance

    ActivityActive
    ResponsivenessResponsive