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Agentgateway

Open source proxy built on AI-native protocols (MCP & A2A) that provides drop-in security, observability, and governance for agent-to-LLM, agent-to-tool, and agent-to-agent communication across any framework and environment.

A 88/100 GitHub score ? This grade is derived from GitHub signals, not user votes. Open for the full breakdown.
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01 / Summary

About Agentgateway.

Agentgateway is a proxy that sits between agents and the things they talk to: LLM providers, MCP tool servers, other agents over the A2A protocol, and ordinary HTTP, gRPC, and TCP services. It puts all of that traffic in one data plane, so routing, authentication, policy, rate limiting, and telemetry are applied in one place instead of across separate gateways.

For LLM traffic it exposes a unified OpenAI-compatible API in front of providers such as OpenAI, Anthropic, Gemini, Bedrock, and Vertex, with budget and spend controls, prompt enrichment, load balancing, and failover. For self-hosted inference it routes to model servers such as vLLM, TGI, and Triton using Kubernetes Inference Gateway extensions, deciding on GPU utilization, KV cache, LoRA adapters, and queue depth.

For MCP it federates tools from multiple servers over stdio, HTTP, SSE, and Streamable HTTP transports, turns OpenAPI services into tools, and adds OAuth authentication. For A2A it handles capability discovery, modality negotiation, and task collaboration between agents built on frameworks such as LangChain, CrewAI, and ADK.

It runs standalone from a flat YAML configuration or on Kubernetes with a built-in controller and Gateway API support, and includes an admin UI for exploring agent-to-agent and agent-to-tool connections and testing routes. Agentgateway is a Linux Foundation project and has joined the Agentic AI Foundation.

  • LLM gateway: one OpenAI-compatible API in front of OpenAI, Anthropic, Gemini, Bedrock, and other providers, with spend controls, load balancing, and failover
  • MCP gateway: tool federation across MCP servers, stdio, HTTP, SSE, and Streamable HTTP transports, OpenAPI integration, and OAuth authentication
  • A2A gateway: agent-to-agent communication with capability discovery, modality negotiation, and task collaboration
  • Inference routing: routing to self-hosted models via Kubernetes Inference Gateway extensions, based on GPU utilization, KV cache, LoRA adapters, and queue depth
  • Guardrails: content filtering with regex, OpenAI moderation, AWS Bedrock Guardrails, Google Model Armor, and custom webhooks
  • Security: JWT, API key, and OAuth authentication, fine-grained RBAC with a CEL policy engine, rate limiting, and TLS
  • Observability: OpenTelemetry metrics, logs, and traces
  • Service traffic: HTTP, gRPC, and TCP routing with mTLS and OIDC
  • Deployment modes: standalone with YAML configuration, or Kubernetes with a built-in controller and Gateway API
  • Admin UI: explore connections and send test prompts to see which backend served a request

02 / Discussion CREDIBILITY-GATED

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