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Alternatives to mcp-repo-graph

  • A
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    CodeGraph — Open-source code intelligence MCP server. Builds a semantic graph of your codebase (functions, classes, imports, call chains) and exposes it through 31 tools. Callers, callees, impact analysis, complexity metrics, unused code detection, AI context assembly, persistent memory, cross-project search. 15 languages via tree-sitter. Single Rust binary, local-first.
    203 npm
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    A powerful Model Context Protocol server that creates intelligent graph representations of your codebase with comprehensive semantic analysis capabilities, supporting 11 languages and 26 MCP methods.
    48 npm
    122
    MIT
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    An MCP server that transforms codebases into knowledge graphs using Neo4J, enabling AI assistants to understand code structure, relationships, and metrics for more context-aware assistance.
    28
    MIT
  • A
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    A fully featured coding agent that uses symbolic operations (enabled by language servers) and works well even in large code bases. Essentially a free to use alternative to Cursor and Windsurf Agents, Cline, Roo Code and others.
    29
    43,883 PyPI
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    GPL 3.0

Related Servers

  • A
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    Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.
    MIT
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    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
    MIT
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    Provides semantic code search and code insights via a knowledge graph, enabling AI to understand, navigate, and modify complex projects with deep dependency and architecture analysis.
    MIT
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    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.
    3 npm
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    Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.
    6
    27 PyPI
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TDQS

A4.4/5.0

Scored across 6 tools

Disambiguation5/5

Each tool targets a clearly distinct action: refresh builds the graph, orient gives context, find discovers nodes, read exposes source, impact computes dependencies, and trace follows cross-boundary paths. No two tools overlap in purpose, and the verbs map cleanly to separate phases of graph-assisted analysis.

Naming Consistency5/5

All six tools use single, lowercase imperative verbs (read, refresh, find, impact, orient, trace), which is a consistent and predictable convention. There are no mixed styles or awkward noun-verb hybrids.

Tool Count5/5

Six tools is well-scoped for a code-graph server; each covers a core operation (build, orient, discover, inspect, impact, trace) without redundancy. Nothing feels missing or gratuitous.

Completeness5/5

The surface covers the full analysis lifecycle: refresh builds and updates the graph, orient provides context, find locates nodes, read exposes source, impact computes blast radius, and trace follows cross-stack flows. For a read/analysis-oriented server, no create/update/delete operations are needed, and the set avoids dead ends.

Maintenance

ActivityMaintained
ResponsivenessSlow