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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.

9,443 servers. Last updated -

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Matching MCP servers:

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    Persistent memory and pattern learning for AI coding assistants via MCP.
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    Enables comprehensive academic research by searching and analyzing papers from PubMed, Google Scholar, ArXiv, and JSTOR. Provides full-text access, citation management, and research organization through five powerful consolidated tools.
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    A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.
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    A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.
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    MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution
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    All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...
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    Provides comprehensive access to Roam Research's API functionality. This server enables AI assistants like Claude to interact with your Roam Research graph through a standardized interface.
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    A local MCP server that enables AI applications like Claude Desktop to securely access and work with Obsidian vaults, providing capabilities for reading notes, executing templates, and performing semantic searches.
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    The server functions as an MCP server to interact with Notion for retrieving and creating survey data, integrating with the Claude Desktop Client for conducting and reviewing surveys.
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    Apache 2.0
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    Deep Research for crypto - free & fully local 🧠
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    MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.
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    An MCP server that enhances Brave Search results by using Puppeteer to extract full webpage content and explore linked pages, enabling AI assistants to perform comprehensive web research with configurable depth.
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    Model Context Protocol (MCP) server that provides AI assistants with advanced web research capabilities, including Google search integration, intelligent content extraction, and multi-source synthesis.
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    A Model Context Protocol compliant server that facilitates comprehensive web research by utilizing Tavily's Search and Crawl APIs to gather and structure data for high-quality markdown document creation.
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    A Model Context Protocol server that enables Claude Desktop to read from and write to Roam Research graphs, allowing for retrieving page content, finding references, and adding blocks to existing or daily pages.
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    An MCP (Model Context Protocol) server implementation using HTTP SSE (Server-Sent Events) connections with built-in utility tools including echo, time, calculator, and weather query functionality.
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    Enables iterative deep research by integrating AI agents with search engines, web scraping, and large language models for efficient data gathering and comprehensive reporting.
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    Enables discovery and analysis of research ecosystems by extracting metadata from paper URLs, GitHub repositories, and research names. Automatically finds related papers, code repositories, models, datasets, and authors across platforms like arXiv, HuggingFace, and GitHub.
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    A server that allows AI assistants to perform web searches using Perplexity's sonar-deep-research model with citation support.
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    Facilitates searching and accessing programming resources across platforms like Stack Overflow, MDN, GitHub, npm, and PyPI, aiding LLMs in finding code examples and documentation.
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    An MCP-based messaging system that allows AI systems to interact with various messaging platforms through standardized tools for sending text, images, documents, buttons, and alerts.
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    A Model Context Protocol server that performs comprehensive web research by combining Tavily Search and Crawl APIs to gather extensive information and provide structured JSON output tailored for LLMs to create detailed markdown documents.
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    An agent-based tool that provides web search and advanced research capabilities including document analysis, image description, and YouTube transcript retrieval.
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    Provides specialized AI-powered comprehensive research and analysis capabilities by integrating with advanced deep research agents, offering unlimited queries with no rate limits and faster performance than comparable services.
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    A multi-model research agent platform supporting Claude, Gemini, and OpenAI models with web search capabilities, thinking-enabled features, and citation support for advanced research workflows.
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    A comprehensive toolkit for Ethereum blockchain analysis within Claude AI, enabling contract auditing, wallet analysis, profitability tracking, and on-chain data retrieval.
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    An adaptation of the MCP Sequential Thinking Server designed to guide tool usage in problem-solving. This server helps break down complex problems into manageable steps and provides recommendations for which MCP tools would be most effective at each stage.
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    MIT License
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    A Model Context Protocol server that provides tools for searching arXiv papers and managing research paper information with local storage capabilities.
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    A dynamic MCP server that automatically discovers Python files in a directory and exposes them as tools to any MCP-compatible AI client, allowing users to easily create and deploy custom AI tools.
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    Model Context Protocol server for interacting with the HaloPSA API, enabling AI assistants like Claude to manage tickets, users, and assets in HaloPSA through natural language.
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    MIT License
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    A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.
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    mcp using PyPDF2 to: • merge-pdfs • extract-pages • search-pdfs • merge-pdfs-ordered (merge in user spec. order) • find-related-pdfs (regex extracted text for related PDF files)
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    The Unlicense