An open-source implementation of the Model Context Protocol (MCP) that bridges AI agents with enterprise systems, enabling secure access to real-world data and capabilities.
A Model Context Protocol server that connects multiple AI models into a single workflow, enabling multi-model orchestration, conversation continuity, and tools like code review, planning, and CLI-to-CLI bridging.
An open-source MCP gateway for AI operators, connecting any LLM to a hot-reloadable connector registry with production-grade approval gates and a built-in control plane for session management.
A testing environment for Model Context Protocol that enables exploration of MCP capabilities and integration of AI models with external data sources and tools.
Facilitates interaction and context sharing between AI models using the standardized Model Context Protocol (MCP) with features like interoperability, scalability, security, and flexibility across diverse AI systems.
A Model Context Protocol server that provides AI models with structured access to external data and services, acting as a bridge between AI assistants and applications, databases, and APIs in a standardized, secure way.