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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.

9,444 servers. Last updated -

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Matching MCP servers:

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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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    Enables users to search for academic articles on platforms like arXiv using specific keywords, with plans to integrate more scholarly databases in the future.
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    An MCP server that connects to the Resource Hub, allowing centralized configuration and management of tools and resources across different MCP environments.
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    An MCP Server that provides a natural language interface to Google Cloud Resource Settings API, enabling users to view and manage settings for Google Cloud resources through conversation.
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    Enables real-time search and retrieval of academic paper information from multiple sources, providing access to paper metadata, abstracts, and full-text content when available, with structured data responses for integration with AI models that support tool/function calling.
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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 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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    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 Model Context Protocol server for querying and analyzing Azure resources at scale using Azure Resource Graph, enabling AI assistants to explore and monitor Azure infrastructure.
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    A Model Context Protocol server providing tools for querying A-share stock market data, including historical prices, financial reports, market indices, and macroeconomic indicators.
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    Deep Research for crypto - free & fully local 🧠
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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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    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 server focused on China's A-share stock market that provides data on stocks, financials, market indices, and macroeconomic indicators.
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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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    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 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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    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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    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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    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 Model Context Protocol server that provides tools for searching arXiv papers and managing research paper information with local storage capabilities.
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    Enables analysis of academic author networks and research collaborations by retrieving co-authors and research keywords from sources like Semantic Scholar, OpenAlex, Crossref, and Google Scholar.
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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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    Enables AI assistants to interact with Hangzhou Dianzi University's academic system through automatic login and course schedule retrieval. Supports secure authentication and structured academic data access for HDU students.
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    Enables AI-powered academic research workflow from keyword search to hypothesis generation. Integrates multiple AI models to automatically search ArXiv papers, extract key information, and generate innovative research hypotheses for researchers.
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    Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.
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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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