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Open-Source MCP servers

Production-ready MCP servers that extend AI capabilities through file access, database connections, API integrations, and other contextual services.

9,449 servers. Last updated -

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Matching MCP servers:

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    An MCP server that enables AI assistants like Claude to access and manipulate Apple Notes on macOS, allowing for retrieving, creating, and managing notes through natural language interactions.
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    MIT License
    • Apple
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    A personal knowledge management system that transforms daily notes into organized, searchable knowledge using the Model Context Protocol.
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    A personal knowledge management system built on the Model Context Protocol that transforms daily notes into organized, searchable knowledge.
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    Enables semantic search and RAG (Retrieval Augmented Generation) over your Apple Notes.
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    Manages markdown notes in a specified directory, allowing users to create, read, update, and list notes through the Model Context Protocol.
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    A Model Context Protocol server that enables semantic search and RAG over your Apple Notes, allowing AI assistants like Claude to search and reference your notes during conversations.
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    • Apple

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    A server that enables Claude to search and access documentation from popular libraries like LangChain, LlamaIndex, and OpenAI directly within conversations.
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    An MCP server for managing and persisting notes, offering CRUD operations, note summarization, and resource-based access via a note:// URI scheme.
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    MIT License
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    A smart documentation server that provides AI-assisted code improvement and documentation management through Claude Desktop integration.
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    A Model Context Protocol server that enables semantic search and retrieval of Apple Notes content, allowing AI assistants to access, search, and create notes using on-device embeddings.
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    • Apple
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    Allows the AI to read from your local Apple Notes database (macOS only)
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    MIT License
    • Apple
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    Enables indexing and retrieving notes with full-text search using SQLite, plus building knowledge graphs to find relationships between concepts. Supports natural language note management, tagging, and semantic connections.
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    Provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
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    MIT License
    • Apple
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    Enables AI assistants to enhance their responses with relevant documentation through a semantic vector search, offering tools for managing and processing documentation efficiently.
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    A server that integrates Retrieval-Augmented Generation (RAG) with the Model Control Protocol (MCP) to provide web search capabilities and document analysis for AI assistants.
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    Apache 2.0
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    Implements a RAG workflow that integrates with any custom knowledge base and can be triggered directly from the Cursor IDE.
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    Implements Retrieval-Augmented Generation (RAG) using GroundX and OpenAI, allowing users to ingest documents and perform semantic searches with advanced context handling through Modern Context Processing (MCP).
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    • Apple
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    Connects a RAG application to open-webui using Model Context Protocol (MCP), enabling server-to-client communication for context retrieval and tool usage in remote environments through Server-Sent Events (SSE).
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    An MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.
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    MIT License
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    A Retrieval-Augmented Generation server that enables semantic PDF search with OCR capabilities, allowing users to query document content through any MCP client and receive intelligent answers.
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    Apache 2.0
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    A complete MCP server for Retrieval-Augmented Generation with file management and vector memory for agents. Supports multiple document formats (PDF, DOCX, TXT, MD, CSV, JSON) with semantic search using Hugging Face embeddings and ChromaDB for efficient vector storage.
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    MIT License
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    An agentic AI system that orchestrates multiple specialized AI tools to perform business analytics and knowledge retrieval, allowing users to analyze data and access business information through natural language queries.
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    "primitive" RAG-like web search model context protocol server that runs locally. ✨ no APIs ✨
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    • Apple
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    A Model Context Protocol server that provides Claude with access to search, retrieve, and analyze notes from the Bear App through natural language queries.
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    Generates comprehensive and formatted release notes from GitHub repositories, efficiently organizing commits by type and including detailed statistics using smart API usage.
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    A Model Context Protocol server that enables intelligent searching across documentation for 30+ programming libraries and frameworks, fetching relevant information from official sources.
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    • Apple
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    An advanced MCP server providing RAG-enabled memory through a knowledge graph with vector search capabilities, enabling intelligent information storage, semantic retrieval, and document processing.
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    • Linux
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    Provides AI agents and coding assistants with web crawling and RAG capabilities, allowing them to scrape websites and perform semantic searches on the crawled content.
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    Enables access to OpenTelemetry documentation by fetching and converting pages to markdown format and searching content using Google Custom Search. Provides comprehensive documentation lookup and search capabilities for OpenTelemetry concepts, instrumentation, and configuration.
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    Apache 2.0
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    Connects Bear Notes to AI assistants using semantic search and RAG (Retrieval-Augmented Generation), allowing AI systems to access and understand your personal knowledge base through meaningful search rather than just keyword matching.
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    • Apple
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    Enables interaction with Apple Notes via natural language, supporting note creation, search, and retrieval with iCloud integration for seamless note management.
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    • Apple
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    Provides tools to access AWS documentation, search for content, and get recommendations for both global and China AWS regions.
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    Apache 2.0