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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.

11,778 servers. Last updated -

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Matching MCP servers:

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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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    A secure Node.js execution environment that allows coding agents and LLMs to run JavaScript dynamically, install NPM packages, and retrieve results while adhering to the Model Control Protocol.
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    Provides C++ code analysis tools for checking naming conventions, include guards, memory safety, const correctness, and modern C++ upgrade suggestions, along with style guide documentation and code review templates.
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    A server that allows LLMs to run Claude Code with all permissions bypassed automatically, enabling code execution and file editing without permission interruptions.
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    Enables asynchronous and parallel execution of Claude Code tasks across multiple sessions, allowing users to start background tasks and continue working immediately without blocking.
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    Executes Python code in isolated rootless containers while proxying MCP server tools, reducing context overhead by 95%+ and enabling complex multi-tool workflows through sandboxed code execution.
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    Executes TypeScript code in a secure sandbox with IPC-bridged access to MCP tools like filesystem operations and network requests.
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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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    Enables AI agents to write and execute Python code in an isolated sandbox that can orchestrate multiple MCP tool calls, reducing context window bloat and improving efficiency for complex workflows.
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    Analyzes C++ source code to automatically generate UML class diagrams in PlantUML format, extracting classes, inheritance relationships, and member visibility from directories or file contents.
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    Model Context Protocol server to run Python code in a sandbox.
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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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    A Python-based system that provides AI-powered code reviews through simulated expert personas like Martin Fowler and Robert C. Martin, using the Model Context Protocol (MCP).
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    Connects Claude Code with Google's Gemini AI, allowing users to ask Gemini questions, get code reviews, and brainstorm ideas directly within Claude Code.
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    MIT License
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    An MCP server to create secure code sandbox environment for executing code within Docker containers.
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    Enables LLMs to interact with MCP servers by writing TypeScript/JavaScript code instead of direct tool calls. Provides a code execution sandbox that accesses MCP servers through HTTP proxy endpoints.
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    This project aims to build a Claude Code MCP server and implement its associated tools (explain\_code, review\_code, fix\_code, edit\_code, test\_code, simulate\_command, your\_own\_query). The server is implemented using Node.js and the MCP SDK. It receives tool requests from clients via Stdio, dynamically
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    Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution.
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    MIT License
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    Integrates Claude Code with DingTalk (钉钉) robot notifications, allowing users to send task completion alerts and various message formats to DingTalk groups from Claude Code.
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    A comprehensive code analysis and management tool that integrates with Claude Desktop to analyze code at project and file levels, helping adapt changes to projects intelligently.
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    MIT License
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    An MCP-compatible server that connects AI agents to SS&C Next Generation, enabling automated execution of business processes via REST API.
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    Enables execution of Go code in the Go Playground sandbox and generation of shareable URLs for code snippets. Provides tools to run Go code, share code via URLs, or perform both operations simultaneously.
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    A Model Context Protocol server that helps large language models process code repositories by providing file tree generation, code merging, and code analysis capabilities.
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    An MCP server that provides semantic search over local git repositories, enabling users to clone repositories, process branches, and search code through vectorized code chunks.
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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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    A smart code retrieval tool based on Model Context Protocol that provides efficient and accurate code repository search capabilities for large language models.
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    Enables AI assistants to review GitLab merge requests by fetching diffs, analyzing code changes, adding comments, and managing approvals through the GitLab API. Supports comprehensive merge request analysis and version comparison for automated code review workflows.
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    MIT License
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    Universal MCP server for executing TypeScript and Python code with progressive disclosure, reducing token usage by 98% by enabling on-demand access to all other MCP tools through code execution rather than loading tool definitions directly.
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    Provides code context and analysis for AI assistants by extracting directory structures and code symbols using WebAssembly Tree-sitter parsers with zero native dependencies.
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