Aggregates multiple Model Context Protocol (MCP) servers into a single, unified proxy interface, supporting real-time discovery, management, and orchestration of AI model resources, tools, and prompts. Enables seamless interaction between MCP clients such as Claude, Cline, and Cursor, while integrating advanced document search, AI document exchange, and workspace management. Provides flexible transport modes (STDIO and Streamable HTTP), robust authentication, and comprehensive security measures for safe and scalable AI data exchange.

• ⭐ 87
• MCP
• VeriTeknik/pluggedin-mcp-proxy

Cloudflare MCP Server enables integration between Cloudflare's suite of services and clients using the Model Context Protocol (MCP). It provides multiple specialized servers that allow AI models to access, analyze, and manage configurations, logs, analytics, and other features across Cloudflare's platform. Users can leverage natural language interfaces in compatible MCP clients to read data, gain insights, and perform automated actions on their Cloudflare accounts. This project aims to streamline the orchestration of security, development, monitoring, and infrastructure tasks through standardized MCP connections.

• ⭐ 2,919
• MCP
• cloudflare/mcp-server-cloudflare

OpenMCP defines a standard for converting various web APIs into servers compatible with the Model Context Protocol (MCP), enabling efficient, token-aware communication with client LLMs. It also provides an open-source registry of compliant servers, allowing clients to access a wide array of external services. The platform supports integration with local and remote hosting environments and offers tools for configuring supported clients, such as Claude desktop and Cursor. Comprehensive guidance is offered for adapting different API formats including REST, gRPC, GraphQL, and more into MCP endpoints.

• ⭐ 252
• MCP
• wegotdocs/open-mcp

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

1MCP Agent provides a single, unified interface that aggregates multiple Model Context Protocol (MCP) servers, enabling seamless integration and management of external tools for AI assistants. It acts as a proxy, managing server configuration, authentication, health monitoring, and dynamic server control with features like asynchronous loading, tag-based filtering, and advanced security options. Compatible with popular AI development environments, it simplifies setup by reducing redundant server instances and resource usage. Users can configure, monitor, and scale model tool integrations across various AI clients through easy CLI commands or Docker deployment.

• ⭐ 96
• MCP
• 1mcp-app/agent

Magg is a server that implements the Model Context Protocol (MCP), acting as a central aggregator and proxy for multiple MCP servers. It enables Large Language Models (LLMs) to dynamically discover, add, configure, and manage external tools at runtime. By aggregating tools from different MCP servers under unified namespaces, it streamlines capability management and introduces features such as configuration persistence, authentication, and real-time notifications. Magg offers both command-line and Docker deployment, with support for HTTP, stdio, and in-memory transport.

• ⭐ 62
• MCP
• sitbon/magg