Open-source gateways designed to manage, route, and secure connections across multiple Model Context Protocol servers.
Archestra is a platform for enterprise AI agent deployment and Model Context Protocol orchestration. It provides a centralized system for configuring specialized agents with specific system prompts and toolsets, and managing the deployment of Model Context Protocol servers that provide large language models with external tools and data sources. The system features an AI agent gateway that exposes configured agents as networked services for external clients and integrated development environments. It incorporates a security suite that provides deterministic guardrails to prevent prompt injecti
Archestra is a dedicated platform for orchestrating and securing Model Context Protocol servers, providing the requested gateway functionality including authentication, observability, and multi-server management in a self-hosted environment.
Higress is an AI API gateway and cloud-native traffic manager that functions as a Kubernetes ingress controller. It provides a centralized system for routing, securing, and optimizing traffic directed toward large language models, AI agents, and microservice architectures. The project distinguishes itself through deep AI orchestration, including the ability to host and manage Model Context Protocol servers that transform REST APIs into tools for AI agents. It features specialized AI infrastructure for model request proxying, protocol translation across multiple providers, and semantic-based c
Higress is a cloud-native AI gateway that natively supports the Model Context Protocol, providing the necessary request routing, security, observability, and orchestration features to manage multiple MCP servers in a centralized environment.
mcp-context-forge is a Model Context Protocol federation gateway that unifies diverse AI tool servers and APIs into a single consistent interface for discovery and execution. It acts as a centralized proxy that aggregates multiple servers and APIs, allowing AI agents to access and invoke a unified set of tools, prompts, and resources. The project distinguishes itself through a multi-protocol translation bridge that converts communication between standard I/O, SSE, gRPC, and REST to enable interoperability between disparate tool servers. It includes a comprehensive LLM evaluation framework for
This is a dedicated federation gateway for the Model Context Protocol that provides the requested orchestration, security, and observability features in a centralized, deployable package.
mcp-use is a development framework designed for building, deploying, and managing servers, clients, and autonomous agents using the Model Context Protocol. It provides a comprehensive toolkit for creating servers that expose custom tools, data resources, and prompts to compatible AI agents. The project distinguishes itself by offering a complete lifecycle for protocol-based applications, including a dedicated hosting platform for production servers and a compliance validator to ensure servers meet marketplace publishing requirements. It also features an observability suite for tracing protoco
This framework provides a comprehensive environment for hosting, securing, and monitoring MCP servers, including features like multi-tenant access control and traffic observability that align with the requirements for a centralized gateway.
Klavis is a platform for managing Model Context Protocol (MCP) servers and providing sandboxed environments where AI agents can safely interact with external tools and services. It functions as an integration framework that orchestrates MCP server instances, exposes tools and resources for AI agents, and isolates agent interactions from production data through horizontally scalable sandbox environments. The platform distinguishes itself through its ability to generate long-horizon agentic tasks that simulate realistic tool-use workflows with live SaaS applications and production MCP servers.
Klavis acts as a centralized platform for orchestrating and managing multiple MCP server instances, providing the necessary authentication, integration, and execution management to serve as a gateway for AI agents.
Bytebot is an LLM desktop automation framework and virtual Linux desktop environment. It enables AI agents to plan and execute mouse and keyboard actions on a virtual computer using natural language, allowing for autonomous desktop automation and the integration of legacy systems that lack native APIs. The system operates as an LLM API gateway and a Model Context Protocol server, routing requests across multiple language model providers with integrated load balancing and rate limiting. It provides isolated, containerized environments where agents use visual reasoning to interpret screenshots
Bytebot functions as an LLM API gateway and MCP server that includes request routing, rate limiting, and orchestration capabilities, making it a suitable tool for managing and securing MCP-based agentic workflows.
The Model Context Protocol SDK is a framework for building clients and servers that connect AI models to external data, tools, and resources using a standardized communication protocol. It provides the foundational libraries and interfaces necessary to establish reliable, transport-agnostic connections between AI agents and external systems, enabling seamless information retrieval and task automation. The SDK distinguishes itself through a robust capability negotiation handshake that ensures compatibility between connected parties before exchanging messages. It supports a pluggable transport
This repository provides the foundational SDK and libraries for building individual MCP clients and servers, rather than acting as a centralized gateway or proxy for orchestrating multiple existing servers.
Ocelot is a .NET API gateway that functions as an HTTP reverse proxy to route, balance, and secure traffic between clients and backend services. It serves as a centralized manager for incoming requests, providing a single entry point for traffic orchestration. The project differentiates itself through dynamic request orchestration, allowing it to aggregate multiple backend service responses into a single result to minimize client network round trips. It also supports dynamic gateway configuration, enabling updates to system behavior and operational parameters without requiring a service resta
Ocelot is a general-purpose HTTP API gateway designed for microservices, but it lacks native support for the Model Context Protocol (MCP) and its specific orchestration requirements.
Django REST Framework is a toolkit for building standards-compliant web services that map complex data models to structured HTTP responses. It provides a modular architecture for handling the request lifecycle, including authentication, permission checks, and content negotiation. The framework is designed to facilitate the development of robust APIs by transforming complex data types into native formats and validating incoming request payloads against defined schemas. The project distinguishes itself through a highly modular, class-based design that allows developers to build complex views an
This is a framework for building RESTful web APIs rather than a specialized gateway or proxy designed to orchestrate and manage Model Context Protocol (MCP) servers.