AgentGateway

aid: agentgateway
name: AgentGateway
description: AgentGateway is an open-source, AI-native proxy and gateway for routing, observing, and governing traffic to and from AI agents, LLM providers, and MCP servers. Built on the A2A and MCP 
  protocols, it provides a unified gateway for LLM consumption, MCP tool federation, agent-to-agent communication, security, and observability. AgentGateway supports multi-provider LLM routing across 
  OpenAI, Anthropic, Google Gemini, AWS Bedrock, and Azure OpenAI with built-in RBAC, JWT authentication, rate limiting, and OpenTelemetry integration.
url: https://raw.githubusercontent.com/api-evangelist/agentgateway/refs/heads/main/apis.yml
humanURL: https://agentgateway.dev/
type: Index
image: https://kinlane-productions.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
- AI Gateway
- API Gateway
- MCP
- LLM
- Agent-to-Agent
- Open Source
- CNCF
- Observability
- Security
created: '2026-03-27'
modified: '2026-04-19'
specificationVersion: '0.19'
apis:
- aid: agentgateway:agentgateway
  name: AgentGateway
  description: AgentGateway provides AI-native gateway capabilities for routing LLM traffic, federating MCP tools, enabling agent-to-agent communication, and applying security and observability 
    controls across AI agent infrastructure.
  humanURL: https://agentgateway.dev/
  baseURL: https://agentgateway.dev
  tags:
  - AI Gateway
  - LLM Routing
  - MCP
  - Agent-to-Agent
  - Security
  - Observability
  properties:
  - type: Documentation
    url: https://agentgateway.dev/docs/
  - type: GettingStarted
    url: https://agentgateway.dev/docs/quickstart/
  - type: GitHubRepository
    url: https://github.com/agentgateway/agentgateway
common:
- type: GitHubOrganization
  url: https://github.com/agentgateway
- type: JSONSchema
  url: https://raw.githubusercontent.com/api-evangelist/agentgateway/refs/heads/main/json-schema/agentgateway-llm-backend-schema.json
  title: LLM Backend Schema
- type: JSONSchema
  url: https://raw.githubusercontent.com/api-evangelist/agentgateway/refs/heads/main/json-schema/agentgateway-mcp-target-schema.json
  title: MCP Target Schema
- type: JSONSchema
  url: https://raw.githubusercontent.com/api-evangelist/agentgateway/refs/heads/main/json-schema/agentgateway-route-schema.json
  title: Route Schema
- type: JSONLD
  url: https://raw.githubusercontent.com/api-evangelist/agentgateway/refs/heads/main/json-ld/agentgateway-context.jsonld
- type: Vocabulary
  url: https://raw.githubusercontent.com/api-evangelist/agentgateway/refs/heads/main/vocabulary/agentgateway-vocabulary.yaml
- type: Portal
  url: https://agentgateway.dev/
- type: Documentation
  url: https://agentgateway.dev/docs/
- type: GettingStarted
  url: https://agentgateway.dev/docs/quickstart/
- type: Support
  url: https://discord.gg/y9efgEmppm
- type: Features
  data:
  - name: LLM Gateway
    description: Routes traffic to OpenAI, Anthropic, Google Gemini, AWS Bedrock, and Azure OpenAI through a unified API with model aliasing, failover, and load balancing.
  - name: MCP Gateway
    description: Connects LLMs to tools via Model Context Protocol with static and dynamic routing, tool federation, and stateful MCP sessions.
  - name: Agent-to-Agent (A2A) Gateway
    description: Enables secure, governed communication between AI agents using the A2A protocol for multi-agent orchestration.
  - name: Inference Routing
    description: Intelligently routes requests to self-hosted models based on GPU utilization and request priority.
  - name: Security and Authentication
    description: Provides JWT, OAuth2, API key management, CORS, CSRF protection, MCP authentication, and external authorization support.
  - name: Traffic Management
    description: Supports request routing and matching, header manipulation, rate limiting, retries, gRPC routing, traffic splitting, and direct responses.
  - name: Observability
    description: Integrates with OpenTelemetry for metrics, traces, and access logging with a built-in Admin UI and debugging tools.
  - name: Guardrails
    description: Applies prompt guards, content filtering, regex filters, moderation policies, and custom webhooks for AI safety.
  - name: Cost Controls
    description: Tracks budget and spend limits per user, team, or application with RBAC-based controls on LLM consumption.
  - name: Prompt Enrichment
    description: Supports prompt templates and enrichment for standardizing and augmenting requests before routing to LLM providers.
- type: UseCases
  data:
  - name: Unified LLM Routing
    description: Route requests across multiple LLM providers with a single API, enabling failover, load balancing, and cost optimization without changing client code.
  - name: MCP Tool Federation
    description: Aggregate tools from multiple MCP servers behind a single gateway endpoint, enabling agents to discover and invoke tools from any connected MCP server.
  - name: Enterprise AI Governance
    description: Apply organization-wide security policies, rate limits, budget controls, and content filters to all AI agent traffic through a centralized gateway.
  - name: REST API to MCP Conversion
    description: Convert existing REST APIs into MCP-native tool endpoints that AI agents can discover and invoke through the Model Context Protocol.
  - name: Multi-Agent Orchestration
    description: Enable secure agent-to-agent communication using the A2A protocol, allowing specialized agents to delegate tasks to each other through the gateway.
  - name: Observability and Debugging
    description: Collect unified telemetry across all AI agent and LLM interactions to monitor cost, latency, and behavior at scale.
- type: Integrations
  data:
  - name: OpenAI
    description: Route to OpenAI GPT models through the AgentGateway LLM backend with model aliasing and budget controls.
  - name: Anthropic
    description: Connect to Anthropic Claude models via the unified LLM gateway with failover and load balancing.
  - name: Google Gemini
    description: Route traffic to Google Gemini models through the AgentGateway multi-provider backend.
  - name: AWS Bedrock
    description: Integrate with AWS Bedrock for managed LLM access via the AgentGateway routing layer.
  - name: Azure OpenAI
    description: Route requests to Azure-hosted OpenAI models through the unified gateway API.
  - name: Ollama
    description: Connect to locally hosted Ollama models for self-hosted inference routing.
  - name: vLLM
    description: Route to vLLM inference servers with GPU utilization-aware routing for optimal performance.
  - name: OpenTelemetry
    description: Export metrics, traces, and logs to any OpenTelemetry-compatible observability backend.
  - name: Kubernetes Gateway API
    description: Deploy and configure AgentGateway on Kubernetes using the standard Gateway API for dynamic configuration.
maintainers:
- FN: Kin Lane
  email: [email protected]