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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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    An MCP server that enables interaction with Markdown knowledge bases, allowing users to search and retrieve content by tags, text, URL, or date range from their local markdown files.
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    A Model Context Protocol (MCP) server for the Open Library API that enables AI assistants to search for book information.
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    Enables access to LDS Gospel Library content and scriptures through the Model Context Protocol. Provides tools for searching and retrieving religious texts and study materials from the Church of Jesus Christ of Latter-day Saints.
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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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    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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    A comprehensive Model Context Protocol server that enables AI assistants to interact with and manage Windows systems, providing capabilities for file system operations, process management, system information retrieval, registry operations, service management, network diagnostics, and performance monitoring.
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    Enables searching and analyzing Facebook's public ads library to see what companies are currently running, including ad images/text, video links, and campaign insights.
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    This MCP server lets you search Facebook's Ad Library, retrieve brand ads, and analyze ad images/videos using AI - all with intelligent caching and batch processing for efficiency.
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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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    Enables AI assistants to maintain persistent conversations and context between sessions through automated saving and global installation across projects. Provides zero-configuration memory persistence with automatic conversation history preservation.
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    A server implementing the Model Context Protocol that provides filesystem operations (read/write, directory management, file movement) through a standardized interface with security controls for allowed directories.
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    Provides Claude with real-time system monitoring capabilities, including CPU, memory, disk, network, battery, and internet speed metrics.
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    Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.
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    A comprehensive MCP (Model Context Protocol) server for file system operations, providing Claude and other AI assistants with access to local files and directories.
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    A Node.js-based AI agent system using Model Context Protocol (MCP) that provides financial analysis and portfolio management services through LangChain and Ollama-powered local AI models.
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    Server that enables AI assistants to interact with Storybook design systems. Extract component HTML, analyze styles, and help with design system adoption and refactoring.
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    Enables Large Language Models to retrieve Jewish texts and commentaries from the Sefaria library through a standardized interface.
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    Enables bidirectional synchronization between IDEs and Figma for Design System management, allowing developers to generate React components and synchronize design tokens, icons, and components across platforms.
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    A high-performance Model Context Protocol (MCP) server built with Go that provides POSIX system monitoring capabilities for Claude Desktop, Cursor, and other MCP clients.
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    A persistent AI conversation system that uses OpenAI's API integrated with Upstash Redis for session storage, allowing users to maintain context across multiple conversations with support for tool integration via MCP architecture.
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    A simple AI development tool that helps users interact with AI through natural language commands, offering 29 tools across thinking, memory, browser, code quality, planning, and time management capabilities.
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    Enables translation of JSON i18n files to multiple languages using various AI providers (Google Gemini, OpenAI, Ollama/DeepSeek) with intelligent caching and deduplication.
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    Provides AI assistants with intelligent access to ML textbook content for creating accurate, source-grounded documentation using local models for privacy and cost efficiency.
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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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    A Model Context Protocol server implementation that provides a standardized interface for interacting with Smallest.ai's knowledge base management system.
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    Enables searching for AI agents by keywords or categories, allowing users to discover tools like coding agents, GUI agents, or industry-specific assistants across marketplaces.
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    A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.
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    Enables intelligent Kubernetes deployments, automated documentation testing, organizational pattern management, and shared prompt libraries. Provides AI-powered recommendations based on cluster capabilities and automates DevOps workflows through conversational interfaces.
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    An advanced system monitoring solution that uses unsupervised machine learning algorithms to detect abnormal resource usage patterns in real-time, with features including anomaly detection, process analysis, and Discord integration.
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    Enables AI assistants to intelligently select and switch between different AI models (OpenAI, Anthropic, etc.) within the same conversation based on task requirements. Provides a unified interface for accessing multiple AI providers through a single MCP tool.
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