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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.

11,847 servers. Last updated -

Matching MCP tools:

Matching MCP servers:

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    A Model Context Protocol server that provides LLMs with full read-write access to PostgreSQL databases, allowing both querying and modifying database content with transaction management and safety controls.
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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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    A Model Context Protocol (MCP) server that allows AI models to safely access and interact with local file systems, enabling reading file contents, listing directories, and retrieving file metadata.
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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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    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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    Enables integration with financial transaction data through REST APIs, PostgreSQL databases, and document storage systems. Demonstrates agentic AI capabilities by connecting to Alpha Vantage API and managing financial data through natural language interactions.
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    A Model Context Protocol (MCP) server that enables AI applications to access and analyze local code repositories without manual uploads, providing file listing, content reading, code searching, and project structure analysis capabilities.
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    Enables AI models to perform file system operations (reading, creating, and listing files) on a local file system through a standardized Model Context Protocol interface.
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    Privacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.
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    Connects AI systems to Local Falcon API, enabling access to local SEO reporting tools including scan reports, trend analysis, keyword tracking, and competitor data through the Model Context Protocol.
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    Automates file system operations through natural language commands using a combination of LLM (Ollama), MCP tools, and a Python bridge agent.
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    Enables AI assistants to access and interact with Cursor/VS Code Local History data for file recovery and enhanced context awareness. Provides tools to browse file history, search across snapshots, and restore previous versions of files.
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    Enables safe file system operations including reading, writing, updating, and deleting files with built-in security safeguards, automatic backups, and comprehensive error handling. Provides directory listing, file metadata extraction, and protects against operations on system-critical paths.
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    Enables AI assistants to intelligently search and explore local file systems using native Unix commands (ripgrep, find, ls) with token-optimized output, automatic pagination, and multi-layer security validation.
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    Enables interaction with the local file system and retrieval of system information. Provides tools for listing directories, reading files, getting current time, and basic greeting functionality.
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    Provides Claude Desktop with direct access to your local file system for development tasks, enabling file operations (read, write, edit), directory browsing, command execution, and codebase search within a configured projects directory.
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    Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.
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    This server provides an interface for performing basic file system operations such as navigation, reading, writing, and file analysis, allowing users to manage directories and files efficiently.
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    Provides semantic code search capabilities that run 100% locally using EmbeddingGemma embeddings. Enables finding code by meaning across 15 file extensions and 9+ programming languages without API costs or sending code to the cloud.
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    A simple Model Context Protocol server that enables AI assistants to interact with local file systems, allowing them to read, write, update, and delete files within a specified project directory.
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    Provides HTML file preview and analysis capabilities. This server enables capturing full-page screenshots of local HTML files and analyzing their structure.
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    Connects to Kakao Local API and Kakao Maps, enabling access to location-based services and map functionality in Korea.
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    A production-ready Model Context Protocol server implementation that connects AI assistants to the TON blockchain, allowing them to query wallet balances, transaction details, smart contracts, and other blockchain data.
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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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    This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.
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    Provides 18 tools including calculator operations (add, subtract, multiply, divide, power, sqrt, log, trigonometric functions) and secure sandboxed file operations (read, write, append, delete, list) for LangGraph agents and MCP clients. Features async support, YAML configuration, comprehensive logging, and path traversal protection.
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    Create sandboxed local development environments directly from Github and execute tests, see coverage and more! Supports Python, Node, Bun and many test runners.
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    Enables monitoring and analysis of local application log files with real-time tailing, error tracking, and search capabilities. Perfect for debugging Node.js applications, web servers, or any application that writes to log files through natural language commands.
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    Enables direct interaction with local WordPress development sites through Local by Flywheel database connections. Provides read-only access to WordPress data including posts, users, options, and custom queries for development and analysis.
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    Enables intelligent file searching in local directories using natural language queries. Supports searching by file type, filename patterns, and content across multiple formats including PDF, Word, Excel, and text files with AI-powered relevance scoring.
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    Provides persistent local memory functionality for AI assistants, enabling them to store, retrieve, and search contextual information across conversations with SQLite-based full-text search. All data stays private on your machine while dramatically improving context retention and personalized assistance.
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