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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.

10,645 servers. Last updated -

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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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    An OpenAI API-based MCP server that provides deep thinking and analysis capabilities, integrating with AI editor models to deliver comprehensive insights and practical solutions.
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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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    A Model Context Protocol (MCP) implementation that provides deep filesystem tree visualization and manipulation capabilities. This tool enables efficient navigation and management of complex directory structures, enhancing development workflows with AI-powered file system operations. Compatible with
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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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    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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    Deep directory tree visualization tool enabling efficient visualization of complex directory structures with AI-powered analysis capabilities.
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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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    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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    Apache 2.0
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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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    This is a Model Context Protocol (MCP) server adaptation of LangChain Ollama Deep Researcher. It provides the deep research capabilities as MCP tools that can be used within the model context protocol ecosystem, allowing AI assistants to perform in-depth research on topics (locally) via Ollama
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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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    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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    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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    Pairs Claude Code with Google's Gemini AI for complementary code analysis, enabling intelligent routing where Claude handles local-context operations while Gemini leverages its 1M token context for distributed system debugging and long-trace analysis.
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    Use Tavily Search to search for news pages or images.
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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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    The Search MCP Server enables seamless integration of network and local search capabilities in tools like Claude Desktop and Cursor, utilizing the Brave Search API for high-concurrency and asynchronous requests.
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    Provides access to OpenAI's advanced models (including o3) with integrated web search, Python code interpreter, and combined analysis capabilities. Enables users to perform web searches, execute code in sandboxed environments, and combine search with analysis through natural language.
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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
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    A Model Context Protocol (MCP) server that provides TypeScript development tools for automated refactoring and code analysis.
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    A collection of tools that enhance MCP-based workflows with caching, retry logic, batch operations, and rate limiting capabilities.
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    A Model Context Protocol server that enables AI assistants to interact with Microsoft Outlook for calendar management, email operations, and search functionality.
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    A Python-based MCP server that provides coordinate conversion between latitude/longitude and UTM/TWD97, along with various civil engineering calculation tools for LLM and AI application integration.
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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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    Enables interaction with the Flutter SDK by providing tools to analyze and apply fixes to Dart and Flutter files.
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    Enables searching text across configured local workspaces using ripgrep. Provides secure text search capabilities within defined workspace boundaries through both MCP server and CLI interfaces.
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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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    Image Tools MCP is a Model Context Protocol (MCP) service that retrieves image dimensions and compresses images from URLs and local files using the TinyPNG API. It supports converting images to formats like webp, jpeg/jpg, and png, providing detailed information on width, height, type, and compressi
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    lark-tools-mcp connects Lark and cursor. It provides cursor with the ability to read documents, send messages, process tasks, and perform data analysis.
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    Enables web search capabilities within MCP-compatible LLM clients using the Parallel Search API. Designed for daily use and everyday smaller web-search tasks.
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