Top 5 MCP Gateways for Routing Tools and Context Across LLM Agents
The Model Context Protocol (MCP) has emerged as the standardized framework for connecting AI agents to external tools, APIs, and data sources. However, managing multiple MCP servers across distributed agent deployments introduces complexity around routing, security, and observability. MCP gateways address this by acting as a unified endpoint that routes requests between AI agents and tools while providing governance, policy enforcement, and monitoring capabilities.
Enterprises deploying agentic AI at scale require gateways that handle more than simple routing. They need platforms that combine security-first architectures, intelligent request distribution, and comprehensive observability. Here are the top five MCP gateways that meet these requirements.
1. Bifrost: Enterprise MCP Gateway with Multi-Provider Support
Platform Overview
Bifrost is a high-performance AI gateway that serves as a comprehensive MCP routing layer alongside unified LLM access across 20+ providers. Bifrost provides enterprise-grade infrastructure for routing tool calls and contextual data flows between agents and external systems.
Key Features
Bifrost's architecture centers on seamless tool integration through MCP support combined with intelligent request routing. The platform offers automatic failover between provider APIs, load balancing across multiple API keys, and semantic caching to reduce latency and cost. Its extensible middleware system supports custom plugins for analytics, monitoring, and specialized routing logic.
Security features include hierarchical budget management, fine-grained access control, SSO integration with Google and GitHub, and native support for HashiCorp Vault for API key management. The observability suite provides Prometheus-compatible metrics, distributed tracing, and comprehensive request logging.
Best For
Teams building multi-agent systems that require both LLM provider flexibility and sophisticated tool routing. Bifrost excels when organizations need a single gateway to manage both model access and agent-to-tool communication while maintaining enterprise compliance requirements.
2. Docker MCP Gateway: Containerized Tool Orchestration
Platform Overview
Docker's MCP gateway is a production-grade, open-source solution designed for organizations already invested in containerized infrastructure. It functions as a centralized orchestration layer that manages MCP server routing and policy enforcement within Kubernetes or Docker Compose environments.
Key Features
The gateway provides centralized routing and discovery of MCP servers from the Docker catalog, simplifies deployment through familiar Docker Compose configurations, and enables policy enforcement at the gateway level. It supports dynamic service discovery and integrates seamlessly with existing container orchestration workflows.
Best For
Organizations with established Docker and Kubernetes infrastructure seeking to integrate MCP without introducing new deployment paradigms. This gateway is ideal for teams prioritizing operational consistency with existing containerized environments.
3. Lasso MCP Gateway: Security-First Proxy Architecture
Platform Overview
Launched in April 2025, Lasso MCP Gateway is an open-source security-first proxy that centralizes MCP traffic routing while providing plugin-based guardrail enforcement. The platform functions as a central orchestration layer between AI agents and multiple tool endpoints.
Key Features
Lasso emphasizes security through customizable plugins for request and response validation. The platform includes structured logging of all tool calls and prompts in JSON format, enabling integration with enterprise monitoring stacks like ELK and Prometheus. It supports multiple transport protocols including HTTP, WebSocket, SSE, and STDIO, accommodating diverse deployment environments.
Best For
Security-conscious organizations requiring auditable tool invocation trails and enforcing data protection policies across agent-tool interactions. Lasso's plugin architecture suits teams needing custom guardrails like PII detection or sensitive data sanitization.
4. ContextForge: Federated Tool and API Gateway
Platform Overview
IBM's ContextForge is a community-driven open-source MCP gateway that federates any MCP server, REST API, or gRPC service into a unified endpoint. The platform functions as both a gateway and a registry, enabling centralized discovery and governance of available tools.
Key Features
ContextForge supports MCP, REST, and gRPC-to-MCP translation, allowing heterogeneous tool ecosystems to be accessed through a single interface. It provides 40+ plugins for extensibility, OpenTelemetry tracing for distributed observability, and Kubernetes-native deployment with Redis-backed federation for multi-cluster scaling.
Best For
Enterprises with diverse tool ecosystems combining modern MCP servers with legacy REST APIs and gRPC services. ContextForge's federated approach is ideal for teams needing to unify tools across multiple architectural paradigms within a single gateway layer.
5. Envoy AI Gateway: Enterprise-Grade Data Plane
Platform Overview
Built in collaboration with Bloomberg and Tetrate, Envoy AI Gateway brings battle-tested proxy infrastructure to MCP routing. The platform extends Envoy Gateway with AI-specific extensions, providing full Model Context Protocol compliance alongside proven enterprise networking capabilities.
Key Features
Envoy AI Gateway leverages the Envoy Proxy data plane for connection management and load balancing while adding MCP-specific session handling, request multiplexing, and stateful JSON-RPC protocol support. The platform integrates with existing Envoy infrastructure and provides fine-grained authentication, authorization, and observability for tool invocations.
Best For
Large enterprises already using Envoy Proxy infrastructure who need MCP support without introducing separate gateway technology. This solution is suited for organizations requiring the highest levels of observability, resilience, and policy enforcement.
Selecting the Right MCP Gateway for Your Needs
Choosing an MCP gateway depends on your infrastructure maturity, security requirements, and tool ecosystem complexity. Teams with sophisticated multi-agent deployments requiring both LLM routing and tool management should evaluate platforms offering integrated observability and governance capabilities.
When evaluating MCP gateways, prioritize platforms that provide comprehensive monitoring of agent-to-tool interactions. Understanding how your agents invoke tools, measuring success rates across different tool types, and identifying failure patterns requires strong observability capabilities.
Beyond the gateway itself, teams should implement evaluation frameworks to monitor agent quality in production. This ensures that tool routing decisions and context flows actually improve agent performance. Platforms like Maxim can complement your MCP gateway by providing agent observability and simulation capabilities to measure the impact of tool integrations.
Get Started with MCP Gateway Evaluation
Implementing the right MCP infrastructure is critical for scaling agentic AI reliably. Whether you choose Bifrost, Docker MCP Gateway, Lasso, ContextForge, or Envoy AI Gateway, the foundation should include comprehensive observability and governance capabilities.
To learn how to evaluate and monitor your AI agents across tool integrations, book a demo and discover how to measure agent quality in production.
