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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.

11,709 servers. Last updated -

Matching MCP tools:

Matching MCP servers:

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    An MCP server that generates comprehensive Learning Hour content for Technical Coaches, enabling teams to practice technical excellence through structured deliberate practice sessions.
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    Runs a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.
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    Generates personalized learning paths by integrating with YouTube, Google Drive, and Notion to create comprehensive learning experiences based on user goals.
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    TypeScript-based MCP server designed to enhance code editing experiences by providing features such as hover information, code completion, and diagnostics.
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    MIT License
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    A comprehensive tutorial project that teaches Model Context Protocol (MCP) development from beginner to advanced levels, covering both server-side and client-side development.
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    Enables autonomous learning from interactions through pattern recognition and machine learning techniques. Continuously improves performance by analyzing tool usage, providing predictive suggestions, and sharing knowledge across MCP servers.
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    A minimal MCP server that enables searching through pre-scraped React documentation using a hybrid approach combining DuckDB full-text search and transformer-based reranking.
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    Exposes VSCode's Language Server Protocol features through MCP, enabling AI assistants to perform language-aware operations like symbol navigation, reference tracking, safe renaming, type information retrieval, and hover documentation across codebases.
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    A Streamlit-based web application that generates personalized learning paths by integrating with YouTube, Google Drive, and Notion services through the Model Context Protocol.
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    A tutorial MCP server for learning the Model Context Protocol by building file and system tools. Provides hands-on experience creating custom tools that enable AI models to interact with files and execute system commands.
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    A comprehensive learning platform for Model Context Protocol development that teaches MCP concepts through hands-on modules including text processing, file operations, and database integration. Designed as an educational tool with progressive difficulty levels from basic to advanced MCP server development.
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    Enables intelligent image analysis using GLM-4.5V model, specializing in extracting and analyzing code from screenshots with support for file paths and clipboard input.
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    A hands-on demonstration project that teaches the Model Context Protocol (MCP) through Python code, allowing users to understand how AI models interact with their context through a provider-agent architecture.
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    A comprehensive educational server demonstrating Model Context Protocol capabilities for tools, resources, and prompts, allowing AI assistants to connect to external data and functionality.
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    A comprehensive learning project providing hands-on experience with Model Context Protocol (MCP) server development, featuring calculator and text utility tools for integration with Claude Desktop.
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    A Model Context Protocol (MCP) server that converts natural language queries into SQL statements, allowing users to query MySQL databases using conversational language instead of writing SQL code.
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    A custom MCP server that provides AI applications with access to an Artificial Virtual Assistant (AVA) toolset, enabling Gmail integration and task management through natural language.
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    Enables users to query ClinicalTrials.gov using natural language instead of complex API parameters, translating plain English requests into structured API calls and returning organized clinical trial data.
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    Enables users to generate and execute InfluxDB queries using natural language commands in Korean. Supports querying metrics like CPU usage, memory status, and system monitoring data through conversational interface.
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    Enables LLM-powered agents to generate, execute, and analyze Alloy modeling language code for software modeling and formal verification. Provides tools to run Alloy models, access documentation and examples, and generate models from system descriptions.
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    A Model Context Protocol server that enables fetching and processing images from URLs, local file paths, and numpy arrays, returning them as base64-encoded strings with proper MIME types.
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    A Model Context Protocol server that enables searching YouTube videos, retrieving and storing transcripts, and performing semantic search over video content without using the official YouTube API.
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    An MCP server that allows coding agents to look up contextual rules and patterns on demand, providing just-in-time guidance for specific tasks like writing tests or authoring UI.
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    A FastMCP integration with Hyperskill that allows AI agents to explain programming topics and search for programming resources using Hyperskill's learning materials.
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    Fetches package documentation from multiple language ecosystems (JavaScript, Python, Java, Ruby, PHP, Rust, Go, Swift, etc.) without requiring API keys, extracting READMEs, API docs, and code examples for LLM analysis.
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    Enables LLMs to autonomously retrieve and explore web content by fetching pages and recursively following links to a specified depth, particularly useful for learning about topics from documentation.
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    A Message Control Protocol server that runs PHP tests and static analysis tools automatically for developers, providing results directly to AI assistants in Cursor editor.
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    MIT License
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    A bridge that provides AI assistants with access to WaniKani user data and functionality, enabling them to retrieve learning progress, identify difficult items, and offer personalized Japanese language learning assistance.
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    Provides AI systems with access to Onyx programming language documentation through web crawling and intelligent search capabilities.
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    Enables AI assistants to analyze personal financial data from Open Banking sources stored in PostgreSQL database. Provides educational financial analysis tools with intelligent formatting for learning about spending patterns, account balances, and transaction history.
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    Enables solving linear programming (LP) and mixed-integer linear programming (MILP) optimization problems through natural language, with built-in simplex and branch-and-cut solvers plus infeasibility diagnostics. Includes optional OR-Tools fallback for larger problems and supports parsing optimization problems from natural language descriptions.
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    MIT License