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Agentgateway

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Overview

Agentgateway is an open source proxy built on AI-native protocols that provides drop-in security, observability, and governance for agent-to-LLM, agent-to-tool, and agent-to-agent communication.

Key Features

  • LLM Gateway: Route traffic to major LLM providers through a unified OpenAI-compatible API with budget controls, load balancing, and failover.

  • MCP Gateway: Connect LLMs to tools and external data sources via MCP with tool federation, OpenAPI integration, and OAuth authentication.

  • A2A Gateway: Secure agent-to-agent communication using A2A with capability discovery and task collaboration.

  • Inference Routing: Intelligent routing to self-hosted models using Kubernetes Inference Gateway extensions based on GPU utilization, KV cache, and queue depth.

  • Guardrails: Multi-layered content filtering with regex, OpenAI moderation, AWS Bedrock Guardrails, Google Model Armor, and custom webhooks.

  • Security & Observability: Auth (JWT, API keys, OAuth), fine-grained RBAC with CEL policy engine, rate limiting, TLS, and OpenTelemetry metrics/logs/tracing.

Use Cases

Routing and securing traffic between AI agents, LLMs, and external tools/services. Providing a unified gateway for agent-to-agent and agent-to-tool communications with embedded security, routing logic, and observability out-of-the-box.

Getting Started

Check the standalone or Kubernetes quickstart guides on agentgateway.dev to deploy the proxy using a flat YAML config or the built-in Kubernetes controller.

Recent Updates

Release v1.5.0 introduces numerous enhancements including support for forward proxy authentication, limit on authorized models per API key, connecting tunneling through dynamic proxy backends, and API-key scoped budgets for LLM traffic. It also includes UI fixes and various security refinements.

Did You Know?

Agentgateway describes itself as the first complete connectivity solution for Agentic AI.