FastMCP is a production-ready framework for building Model Context Protocol (MCP) applications in Python. It streamlines the creation of MCP servers and clients, providing advanced features such as enterprise authentication, composable tools, OpenAPI/FastAPI generation, server proxying, deployment tools, and comprehensive client libraries. Designed for ease of use, it offers both standard protocol support and robust utilities for production deployments.

• ⭐ 20,201
• MCP
• jlowin/fastmcp

MCP Router is a cross-platform desktop application designed to simplify the management of Model Context Protocol (MCP) servers. It enables users to centrally manage, organize, and monitor multiple MCP servers, both locally and remotely, with support for various connection methods. The app offers advanced context organization through Projects and Workspaces, as well as tools toggling and comprehensive logging. With a focus on privacy, all data is stored locally, and integration capabilities allow seamless connection with popular AI tools.

• ⭐ 1,078
• MCP
• mcp-router/mcp-router

Mastra is a modern TypeScript-based framework designed for developing AI-powered applications and autonomous agents. It offers model routing to integrate over 40 AI providers, a graph-based workflow engine, advanced context management, and production-ready tools for observability and evaluation. Mastra features built-in support for authoring Model Context Protocol (MCP) servers, enabling standardized exposure of agents, tools, and structured AI resources via the MCP interface.

• ⭐ 18,189
• MCP
• mastra-ai/mastra

AWS MCP Servers is a suite of specialized servers implementing the open Model Context Protocol (MCP) to bridge large language model (LLM) applications with AWS services, tools, and data sources. It provides a standardized way for AI assistants, IDEs, and developer tools to access up-to-date AWS documentation, perform cloud operations, and automate workflows with context-aware intelligence. Featuring a broad catalog of domain-specific servers, quick installation for popular platforms, and both local and remote deployment options, it enhances cloud-native development, infrastructure management, and workflow automation for AI-driven tools. The project includes Docker, Lambda, and direct integration instructions for environments such as Amazon Q CLI, Cursor, Windsurf, Kiro, and VS Code.

• ⭐ 6,220
• MCP
• awslabs/mcp

MCP Link enables automatic conversion of any OpenAPI v3-compliant RESTful API into a Model Context Protocol (MCP) server, allowing instant compatibility with AI-driven agent frameworks. It eliminates the need for manual interface creation and code modification by translating OpenAPI schemas into MCP endpoints. MCP Link supports robust feature mapping and authentication, making it easy to expose existing APIs to AI ecosystems using a standardized protocol. The tool is designed for both developers and organizations seeking to streamline API integration with AI agents.

• ⭐ 572
• MCP
• automation-ai-labs/mcp-link

Lara Translate MCP Server enables AI applications to seamlessly access professional translation services via the standardized Model Context Protocol. It supports features such as language detection, context-aware translations, and translation memory integration. The server acts as a secure bridge between AI models and Lara Translate, managing credentials and facilitating structured translation requests and responses.

• ⭐ 76
• MCP
• translated/lara-mcp