The OmniMesh Gateway serves as a robust, central hub for managing tools, resources, and prompts specifically designed for Model Context Protocol (MCP)-compatible Large Language Models (LLMs). It acts as a sophisticated API gateway that can translate standard REST APIs into the MCP format, facilitating the creation of virtual MCP servers. Engineered for enterprise-grade deployments, it integrates comprehensive security features including JWT, OAuth2, and OIDC authentication with RBAC, API key management, and intelligent rate limiting. The gateway also offers dynamic server discovery, namespace management for isolating services, and extensive support for various communication protocols such as JSON-RPC 2.0, WebSocket, Server-Sent Events, Streamable HTTP, and STDIO. Furthermore, it provides critical observability capabilities through detailed audit trails, performance metrics, and session tracking, ensuring a secure and scalable infrastructure for AI agents.
Key Features
01Comprehensive logging, auditing, and performance metrics with external integration options
02Secure authentication (JWT, OAuth2, OIDC) with RBAC and API Key Management
03Service virtualization to transform REST APIs into MCP tools with schema validation
04Dynamic MCP server discovery and isolated namespace management
0526 GitHub stars
06Multi-protocol transport support (JSON-RPC 2.0, WebSocket, SSE, Streamable HTTP, STDIO)
Use Cases
01Transforming existing HTTP services into MCP-compliant tools with added security and observability
02Centralized management and exposure of tools, resources, and prompts for MCP-compatible LLMs
03Securing and optimizing access to internal or external AI agent services
