Skip to main content
Glama
James-Chahwan

mcp-repo-graph

by James-Chahwan
OverviewSchemaSourceRelated ServersDiscussions(1)Admin
Python
Hybrid

Related Servers

Alternatives to mcp-repo-graph

  • CodeGraph

    codegraph-ai
    A
    license
    Not graded
    quality
    Not graded
    maintenance
    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.
    248 npm
    -

  • code-graph-rag-mcp

    er77
    A
    license
    Not graded
    quality
    F
    maintenance
    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.
    58 npm
    122
    MIT

  • CodeRAG

    JonnoC
    A
    license
    Not graded
    quality
    D
    maintenance
    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

  • Serena

    oraios
    A
    license
    A
    quality
    A
    maintenance
    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
    42,914 PyPI
    29,226
    MIT

Related Servers

  • XRAY MCP

    srijanshukla18
    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
    MIT

  • code-intel

    nairraf
    A
    license
    Not graded
    quality
    B
    maintenance
    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

  • mcp-codebase-intelligence

    g-tiwari
    A
    license
    Not graded
    quality
    B
    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.
    11 npm
    1
    MIT

  • archiet-xray

    Anioko
    A
    license
    A
    quality
    C
    maintenance
    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
    MIT

  • CodeGraph

    colbymchenry
    A
    license
    Not graded
    quality
    A
    maintenance
    Supercharges AI coding agents with a pre-indexed semantic code graph, enabling instant symbol relationships, impact analysis, and context retrieval across 20+ languages.
    73,805 npm
    70,212
    MIT
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.4/5.0

Scored across 6 tools

Disambiguation5/5

Each tool has a distinct purpose: find resolves text to nodes, impact shows dependency blast radius, orient provides overviews, read retrieves source code, refresh rebuilds the graph, and trace follows cross-boundary flows. There is no overlap in functionality.

Naming Consistency5/5

All tool names are single-word, lowercase imperatives (find, impact, orient, read, refresh, trace) following a consistent verb pattern without any mixing of conventions.

Tool Count5/5

With 6 tools, the server covers all necessary operations for code graph analysis—build, explore, search, read, and trace—without being excessive or insufficient.

Completeness5/5

The tool set covers the full lifecycle: building the graph (refresh), getting oriented (orient), finding nodes (find), reading code (read), analyzing impact (impact), and tracing flows (trace). There are no obvious gaps.

Maintenance

ActivityStale
ResponsivenessSlow

Resources