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Alternatives to codetree

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    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI coding agents to query a pre-built semantic knowledge graph of code, reducing token usage and tool calls. Supports 16 tools for code exploration, analysis, and context building.
      5 npm
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    • 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.
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    • A
      license
      Not graded
      quality
      C
      maintenance
      Provides a semantic understanding of your codebase by parsing with tree-sitter and building a graph of symbols and dependencies. Enables AI assistants to navigate code, analyze changes, and discover architecture using 18 tools with minimal context overhead.
      9 npm
      1
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    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables LLMs to perform high-performance code search and analysis across multiple languages using symbol indexing, regex text search, and structural AST pattern matching. It also provides tools for technology stack detection and dependency analysis with persistent caching for optimized performance.
      8
      -
    • A
      license
      A
      quality
      D
      maintenance
      Enables AI assistants to understand and navigate codebases through structural analysis. Provides code mapping, symbol search, and impact analysis using ast-grep for accurate parsing of Python, JavaScript, TypeScript, and Go projects.
      4
      52
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    TDQS

    A3.7/5.0

    Scored across 23 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose, with no overlapping or ambiguous functionality. Tools like `get_symbol` and `get_symbols` are differentiated by scope, and `search_graph` vs `search_symbols` target different aspects of the codebase.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., `analyze_dataflow`, `find_references`, `get_call_graph`). Naming conventions are uniform, making the tool set predictable and easy to navigate.

    Tool Count4/5

    With 23 tools, the set is slightly larger than typical but remains well-scoped for a comprehensive code analysis server. Each tool serves a distinct purpose, and the count feels justified by the breadth of analysis features offered.

    Completeness5/5

    The tool set covers the full spectrum of static code analysis: exploration (repository map, skeletons), dependency analysis (call graph, dependency graph), quality checks (complexity, clones, dead code), and context (git history, test finding). No obvious gaps for the stated purpose.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues