"Official GitHub MCP server" matching MCP servers:

Official Telys MCP server: private, on-device AI memory and retrieval powered by native Mojo kernels. 19 tools: memory CRUD, semantic + BM25 search, single-key filters, compaction/IVF/tuning and self-refreshing repo auto-indexing. Stdio. Introspection needs no credentials; execution requires a one-time free telys login. Source: packages/telys-sdk/telys/mcp.py. Registry: io.github.thyn-ai/telys.

Gives every AI agent you use one shared, versioned memory in a local SQLite file, so a fact saved from one app is found by all the others. Runs fully offline with no API key, records which agent wrote each change, and keeps every prior version so nothing is silently overwritten.

Enables LLM hosts to retrieve live, relevant documentation excerpts from official library docs sites via a search-and-RAG tool, avoiding reliance on training data.

RAG MCP server for PDFs, YouTube, GitHub repos, and Discord exports. Index documents and query with citations via LangChain and Chroma.

The official Redis MCP Server is a natural language interface designed for agentic applications to efficiently manage and search data in Redis.

Enables GitHub Copilot to query local ChromaDB instances to retrieve relevant documents and context for AI conversations. It allows users to search vector collections using natural language tools directly within VS Code.

Official MCP server for Stoolap, an embedded SQL database written in Rust. Lets assistants run SQL queries and transactions, inspect and change schemas, and do vector search over a local file or in-memory database, with a read-only mode.

Enables GitHub Copilot Chat to semantically search locally indexed source code, documentation, and project statistics from reference projects through a fully local vector store. This lets Copilot find existing implementations and conventions so it generates new code homogeneous with established patterns, without any API keys or data leaving the machine.

Official Kimss MCP server — call your Kimss agents, models, files, and vector stores from Cursor and other MCP clients using your API key.

An MCP server that enables semantic search over a private knowledge base via pgvector, with GitHub OAuth authentication and a RAG pipeline.

Enables agents to search indexed documents and GitHub repository code through stdio-exposed tools, returning relevant evidence for grounded answers and code reviews.

Enables chat.z.ai agents to keep persistent vector memory, auto-enhance context, compress long content to save tokens, and orchestrate smart skills, with every session mirrored to the user's own private GitHub repository as a human-readable cloud database. Exposes these capabilities through a streamable HTTP MCP endpoint with 12 tools, resources, and prompt templates.

Enables Claude Desktop and Claude Code to answer questions about Indian mutual funds from official SEBI, AMC, and AMFI documents by retrieving cited, layout-aware document chunks through hybrid semantic and keyword search.

Adds persistent long-term memory to GitHub Copilot CLI via local semantic vector search, enabling Copilot to recall past conversations and code decisions across sessions.

An MCP server that enables semantic search over local files or GitHub repositories by indexing content into a serverless vector database, allowing AI assistants to understand meaning rather than just keywords.

Enables AI agents to chat with codebases by indexing local directories or GitHub repositories into a vector database for semantic search and code retrieval.

Enables semantic search across indexed documents using vector embeddings. Index GitHub repositories and URLs to perform natural language queries with AI-enhanced contextual results.

A local MCP server that provides persistent, project-scoped semantic memory for GitHub Copilot in VS Code, using ChromaDB and embeddings for RAG-based memory retrieval across sessions.

Integrates with GitHub, Neo4j, PostgreSQL, and Milvus, enabling queries and data retrieval across these services.

Enables AI agents to semantically search GitHub repository documentation by automatically fetching, vectorizing, and indexing content into an Upstash Vector database. It provides a standard MCP interface for agents to retrieve relevant documentation snippets through natural language queries.

Enables hybrid search (dense + sparse) over self-hosted indexes of continuously ingested public datasets (news, GitHub, Wikipedia, arXiv, small web, devdocs, Hacker News) using your own embedding model, served via the Model Context Protocol.

Enables AI assistants like GitHub Copilot to save and retrieve code snippets with semantic vector search, and to launch multi-agent workflows that generate language-specific style guides and comprehensive wiki documentation. It exposes these capabilities as discoverable MCP tools backed by Azure Functions, Cosmos DB vector indexing, and Azure OpenAI.

MCP server to perform semantic and keyword searches across AI Nike-chan's public X posts and official website, with optional AI Gateway integration and vector index hosting on Vercel Blob.

Enables context-aware semantic search across codebases using Qdrant vector database with intelligent GitHub issue resolution, Projects V2 management, and progressive context retrieval for 95%+ token reduction in AI-assisted development.