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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 -

Matching MCP tools:

Matching MCP servers:

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    Model Context Protocol server to run Python code in a sandbox.
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    MIT License
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    Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.
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    MIT License
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    A secure MCP server example that demonstrates how to deploy to Google Cloud Run with authentication and identity token protection. Serves as a tutorial template for building production-ready MCP servers in the cloud.
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    Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.
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    Apache 2.0
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    A Model Context Protocol server that extracts and analyzes Python code structures, focusing on import/export relationships between files to help LLMs understand code context.
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    A server that provides a persistent Python REPL environment through the MCP protocol, allowing execution of Python code, variable management, and package installation.
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    MIT License

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    An MCP server that executes tox commands to run Python tests within a project using pytest, allowing users to run all tests or specific test groups, files, cases, or directories.
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    A collection of Python-based Model Context Protocol servers that extend AI assistant capabilities with tools for calculations, AWS services (S3 and RDS), and PostgreSQL database operations.
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    Provides an interactive Python REPL environment that maintains persistent session state, allowing users to execute Python code and access session history.
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    Enables LLM agents to execute arbitrary Python code in secure, isolated sandbox environments with automatic dependency management and file handling. Each code execution runs in a fresh virtual environment that gets destroyed after completion, providing safe and reproducible Python code execution.
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    MIT License
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    A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.
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    A secure proxy solution for hosting MCP (Model Context Protocol) servers on Google Cloud Run, allowing teams to share access through IAM authentication while bypassing current MCP authentication limitations.
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    Provides accurate Pine Script v6 coding assistance through search, completion, and reference lookup tools using a comprehensive Japanese manual database. Enables developers to quickly find functions, constants, annotations, and API specifications for TradingView Pine Script development.
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    This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.
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    A basic example demonstrating how to develop and run a serverless Model Context Protocol (MCP) implementation using Netlify Functions and Express.
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    Enables MCP-compatible AI agents to deploy applications to Google Cloud Run by providing tools for deploying code, listing services, and managing Google Cloud projects.
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    A Model Context Protocol server that allows LLMs to interact with Python environments, enabling code execution, file operations, package management, and development workflows.
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    A streamlined foundation for building Model Context Protocol servers in Python, designed to make AI-assisted development of MCP tools easier and more efficient.
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    A Python-based server allowing seamless integration with JIRA for managing and interacting with projects through custom APIs.
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    Provides integration with the Google Apps Script API, allowing management of script projects, deployments, versions, and executions through any MCP-compatible client like Claude Desktop or VS Code.
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    A Model Context Protocol server that enables AI assistants like Claude to perform Python development tasks through file operations, code analysis, project management, and safe code execution.
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    A Python implementation of the Model Context Protocol (MCP) server that enables searching and extracting information from arXiv papers, designed to be extensible with additional MCP tools.
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    An MCP server that enables users to fetch Python documentation using the Brave Search API through natural language queries.
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    A demonstration server showing MCP implementation in Python with resource handling, tool operations, and reusable prompts for a simple user/post system with local database.
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    Provides up-to-date Python package manager commands by cross-referencing official pip, poetry, uv, and conda documentation with automatic weekly updates.
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    This MCP server provides unified diffs of two text inputs using Python's standard library difflib.
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    A lightweight Python-based server designed to run, manage and create CrewAI workflows using the Model Context Protocol for communicating with LLMs and tools like Claude Desktop or Cursor IDE.
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    An interactive Python code execution environment that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.
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    A Python server that enables interaction with macOS native applications (Contacts, Notes, Mail, Messages, Reminders, Calendar, and Maps) through AppleScript, featuring asynchronous operations and type-safe interfaces.
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    A Python-based MCP server that uses uv for dependency management, requiring Python 3.13+ to run.
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    Stdio MCP Server wrapping custom Python runtime (LocalPythonExecutor) from Hugging Faces' smolagents framework. The runtime combines the ease of setup (compared to docker, VM, cloud runtimes) while providing safeguards and limiting operations/imports that are allowed inside the runtime.
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    • Apple