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    Related Servers

    • F
      license
      A
      quality
      C
      maintenance
      Provides codebase indexing and retrieval tools that give AI agents token-efficient, query-relevant context packages (symbols, imports, and dependencies) instead of scanning entire repositories.
      6
      -
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables LLM agents to efficiently understand and navigate a codebase by providing semantic search over symbols and a reference graph, replacing expensive grep/glob calls with structured tools like definition lookup, caller/callee queries, and change-impact analysis.
      3
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Indexes a codebase into a symbol-level graph and exposes tools for finding symbols, querying relationships, and assessing impact, letting AI coding agents answer structural questions in a single call within a token budget.
      44 npm
      4
      Apache 2.0
    • A
      license
      Not graded
      quality
      D
      maintenance
      A graph-powered code intelligence engine that indexes codebases into a structural knowledge graph to provide AI agents with deep context on function calls, types, and execution flows. It offers local, zero-dependency tools for hybrid search, impact analysis, and dead code detection across Python, JavaScript, and TypeScript projects.
      1,290 PyPI
      815
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.
      100 npm
      MIT

    TDQS

    A3.8/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool targets a distinct analysis task: repo overview, symbol search/retrieval, file outline, reference lookup, module dependencies, churn hotspots, and diff impact. The overlap between find_references and diff_impact is minimal and contextually separated by change-focused vs. general reference lookup.

    Naming Consistency3/5

    Names use snake_case throughout, but they mix verb_noun (search_symbols, get_symbol, find_references) with noun_phrase (diff_impact, hotspots, repo_summary, file_outline, module_dependencies). The convention is readable but not predictable as a single pattern.

    Tool Count5/5

    Eight tools are well-scoped for a repository analysis server, with no obvious redundancy. Each tool covers a distinct and useful analysis capability, fitting comfortably in the recommended 3-15 range.

    Completeness4/5

    The set covers core static analysis needs: overview, symbol search, symbol retrieval, file outline, references, dependencies, churn, and change impact. Minor gaps exist, such as direct file content reading or type hierarchy/call graph queries, but agents can often work around these using other tools.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues