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Alternatives to tree-lens

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    Related Servers

    • A
      license
      A
      quality
      C
      maintenance
      Enables AI coding agents to efficiently explore codebases by providing structural outlines, module digests, symbol bodies, and AST-aware grep via MCP.
      4
      3,128 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding agents to query code structure efficiently through 16 MCP tools, including symbol lookup, full-text search, dependency analysis, and refactor planning, powered by tree-sitter parsing and index-backed code intelligence.
      3
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables LLM agents to query a codebase's structural knowledge (symbols, imports, call graphs, etc.) via MCP, reducing tokens and improving correctness compared to raw file access.
      119 npm
      7
      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
      A
      maintenance
      Enables AI coding agents to retrieve focused structural context from a local code graph, inspect relationships, and carry project memory across sessions. It serves this context via MCP to reduce token usage while investigating code before making behavioral claims.
      35 npm
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Provides IDE-like coding capabilities for AI agents via MCP, enabling semantic code retrieval, symbol-level editing, refactoring, and navigation across many programming languages.
      MIT

    TDQS

    A3.9/5.0

    Scored across 15 tools

    Disambiguation4/5

    Most tools target clearly distinct operations (read vs list vs search vs index), and descriptions include enough detail to separate them. Minor overlap exists between find_references/callers and go_to_definition/read_definition, but the descriptions identify different granularities and index dependencies.

    Naming Consistency5/5

    All tool names use consistent snake_case with a clear verb_noun or noun form (list_definitions, index_workspace, preset_search, callers, callees). No mixed conventions or vague generic verbs appear.

    Tool Count5/5

    15 tools is well within the appropriate range for a code-analysis server: file-level reading/querying, workspace indexing, reference resolution, call-graph helpers, and presets each have a clear place. The count feels deliberate rather than padded.

    Completeness4/5

    The surface covers the domain well: per-file definitions, AST queries, presets, indexing lifecycle, reference/definition lookup, and call-graph analysis. A minor gap is the lack of workspace-wide AST/search operations and no listing of files/symbols across the workspace, but agents can work around those with existing tools.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues