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"GitHub repository operations: reading files, editing structure, and extracting data" matching MCP servers:

  • A
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    MCP server that provides a citation-first memory layer for AI agents, enabling verified search across Git-backed repositories and optional conversation memory. It exposes tools for doctor, sync, search, get, init, and ingest, returning JSON results with verified citations or abstain status.
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    An MCP server that enables analyzing and querying GitHub repositories through the GitHub Chat API, allowing users to index repositories and ask questions about their code, architecture and tech stack.
    2
    86
    MIT
  • F
    license
    B
    quality
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    maintenance
    An MCP server that allows Claude and other MCP-compatible LLMs to interact with the GitHub API, supporting features like creating issues, getting repository information, listing issues, and searching repositories.
    4
  • A
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    quality
    A
    maintenance
    Enables AI agents to search and retrieve context from GitHub issues, pull requests, releases, and documentation using hybrid semantic search and time-ordered activity scans.
    777
    Apache 2.0
  • A
    license
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    quality
    A
    maintenance
    A personal RAG MCP server that indexes your GitHub commits and review comments, surfacing them as retrieval hits to help Claude Code write or review code in your style.
    MIT
  • A
    license
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    quality
    C
    maintenance
    Enables automated GitHub Pull Request reviews using local Ollama, Cursor CLI, or Gemini CLI as AI providers. Supports customizable review prompts, comprehensive PR analysis, and optional auto-posting of reviews to GitHub.
    10
    5
    MIT
  • F
    license
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    quality
    C
    maintenance
    An MCP server exposing internal business operations as tools — task management (create, list, update status) and RAG-style semantic search over an internal knowledge base (leave, expense, and onboarding policies) that any MCP-compatible AI agent can call directly for grounded, non-hallucinated answers.
  • A
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    quality
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    maintenance
    Enables natural language querying of PostgreSQL via MCP, combining SQL, vector search, and knowledge graph with automatic routing and token-aware curation.
    Apache 2.0
  • F
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    quality
    D
    maintenance
    Enables querying and analyzing user, product, and order data with filtering capabilities and real-time statistics. Supports WebSocket connections to XiaoZhi AI platform with automatic reconnection.
  • F
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    quality
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    maintenance
    Enables AI applications to access and contextualize organizational knowledge sources including GitHub repositories and internal documentation through standardized MCP protocol integration. Features OAuth 2.1 authentication, vector-based semantic search, and optimized context chunking for enterprise development workflows.