"A server for searching GitHub and GitLab" matching MCP servers:

First gitlab mcp for you, building together

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.

A Model Context Protocol server that connects GitHub code to Claude.ai. This server utilizes the Pera1 service to extract code from GitHub repositories and provide better context to Claude.

Enables AI agents to analyze public GitHub repositories directly through tools for repo health scoring, recent commit summaries, good first issue discovery, and semantic Q&A over docs and issues.

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.

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.

Enables natural language search and querying of your GitHub starred repositories.

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.

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.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables managing GitHub starred repositories with semantic search and RAG-based Q&A, along with optional Gitea backup.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables interaction with GitHub repositories through the GitHub API using fastMCP. Supports repository information retrieval and management with secure token-based authentication.

MCP server for GitHub code retrieval and reuse, using SQLite+FTS5 indexing and search history to enable search-first, requirements-refined code search from GitHub repositories.

Enables AI agents to search private GitHub Pages by authenticating in a dedicated browser and retrieving indexed sections from a local SQLite database, with support for multiple sites and languages.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A proof of concept MCP server for Apache OFBiz

Retrieves historical pull request context from GitHub repositories and provides it to IDE agents for reasoning, review, and code generation without modifying files.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

This MCP server provides a cost-optimized personal-knowledge brain, enabling AI agents to query imported documents via hybrid search and synthesis at minimal monthly spend.

Turns any static website into an MCP-searchable knowledge base by deploying a Cloudflare Worker that provides full-text search tools, enabling AI assistants to search and retrieve content from your site.

A local-first RAG system that indexes personal documents and enables querying them via an MCP tool, keeping data private with local embeddings.

Enables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.