Aggregates multiple MCP servers into a single endpoint, enabling LLM clients to access tools, resources, and prompts from various backends through one connection.
Aggregates multiple MCP servers behind a single local endpoint, letting LLM clients connect to one router that exposes a unified set of tools, resources, and prompts.
A dynamic MCP server orchestrator and multiplexer that routes requests to multiple remote and local sub-MCP servers, with hot-reload config, SSE/Streamable HTTP support, and a summary endpoint to reduce context token usage.
Routes requests to multiple downstream Model Context Protocol servers and provides a LangGraph.js-based agent with RAG capabilities for development assistance.
Aggregates multiple Model Context Protocol servers into a single gateway to provide unified search, description, and execution of tools. It reduces context limit issues by dynamically fetching specific tool schemas only when needed rather than loading all available tools at once.
A robust server implementing the Model Context Protocol with SSE and STDIO transport, enabling real-time communication and extensible tooling for AI models.