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Alternatives to minga-graph

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    • A
      license
      Not graded
      quality
      C
      maintenance
      A local knowledge graph of your codebase for Claude Code on macOS, exposing structural data via MCP tools for querying calls, imports, test coverage, and impact analysis.
      90 PyPI
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables coding agents to query a deterministic AST knowledge graph of a codebase over MCP—finding symbols, callers/callees, dependencies, impact, and relevant tests via compact path:line JSON—so they can navigate code without grepping, embeddings, or an LLM.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents to query a local code graph over stdio, so they can see what a Git change may affect, find related tests, routes and nodes, and cite evidence paths — read-only and fully on-machine.
      6 npm
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding agents to query a locally indexed structural code graph — source entities, callers/callees, Git relationships and recorded mistakes — so they retrieve focused, token-bounded context instead of reading entire files. It runs over local SQLite and can be served through a CLI, agent hooks, an MCP executable and an authenticated local dashboard.
      24 npm
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables coding agents to query a local, multi-repo code graph for symbol exploration, blast radius analysis, co-change mining, and durable code-anchored memory via MCP tools.
      128 npm
      16
      Business Source 1.1

    TDQS

    A3.6/5.0

    Scored across 5 tools

    Disambiguation4/5

    Each tool targets a distinct operation: explain one node, path between two, transitive impact, graph metadata, and natural-language query. graph_explain and graph_query could be mildly confused since both return node/edge info, but the 'one specific node' vs 'plain-language question' framing helps separate them.

    Naming Consistency5/5

    All five tools follow the same graph_<verb/noun> pattern (graph_explain, graph_path, graph_impact, graph_stats, graph_query). Predictable and easy to scan.

    Tool Count5/5

    Five focused tools for a read-only graph knowledge service; each earns its place without redundancy or thinness.

    Completeness4/5

    Covers node inspection, traversal, dependency analysis, metadata, and semantic query—full read-only lifecycle for a graph service. A direct node-list/lookup-by-name operation could be a minor convenience gap, but graph_query largely compensates.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues