AgentGateway

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.

AgentGateway publishes 6 APIs on the APIs.io network, including Config API, Debug API, Lifecycle API, and 3 more. Tagged areas include AI Gateway, API Gateway, MCP, LLM, and Agent-to-Agent.

The AgentGateway catalog on APIs.io includes 1 JSON-LD context and 1 Spectral governance ruleset.

AgentGateway’s developer surface includes developer portal, documentation, getting-started guide, support, engineering blog, and 9 more developer resources.

🌐 Visit website 📡 Source on GitHub

47.6/100 developing ▼ -5.3 Agent 22/100 agent aware Full breakdown ↓
scored 2026-07-28 · rubric v0.6

AccessFreemium

7 APIs 10 Features 6 Use Cases

AI GatewayAPI GatewayMCPLLMAgent-to-AgentOpen SourceCNCFObservabilitySecurity

Kin Score

Kin Score How this is scored →
scored 2026-07-28 · rubric v0.6

Composite quality — 47.6/100 · developing

Contract Quality 12.3 / 25

Developer Ergonomics 7.0 / 20

Commercial Clarity 7.9 / 20

Operational Transparency 4.8 / 13

Governance 8.3 / 12

Discoverability 7.4 / 10

Agent readiness — 22/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 10 / 10

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/agentgateway: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

APIs 7

Individual APIs this provider publishes, each with its own machine-readable definition.

AgentGateway

AgentGateway provides AI-native gateway capabilities for routing LLM traffic, federating MCP tools, enabling agent-to-agent communication, and applying security and observabilit...

AgentGateway Config API

The Config API from AgentGateway — 1 operation(s) for config.

AgentGateway Debug API

The Debug API from AgentGateway — 2 operation(s) for debug.

AgentGateway Lifecycle API

The Lifecycle API from AgentGateway — 1 operation(s) for lifecycle.

AgentGateway Logging API

The Logging API from AgentGateway — 1 operation(s) for logging.

AgentGateway Memory API

The Memory API from AgentGateway — 1 operation(s) for memory.

AgentGateway Profiling API

The Profiling API from AgentGateway — 2 operation(s) for profiling.

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Open Collections 1

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

AgentGateway Admin / Debug API

OPEN COLLECTION

Pricing Plans 1

Published pricing tiers and plan structures.

Agentgateway Plans Pricing

3 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Agentgateway Rate Limits

5 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

Agentgateway Finops

FINOPS

Features 10

Notable capabilities this provider offers.

LLM Gateway

Routes traffic to OpenAI, Anthropic, Google Gemini, AWS Bedrock, and Azure OpenAI through a unified API with model aliasing, failover, and load balancing.

MCP Gateway

Connects LLMs to tools via Model Context Protocol with static and dynamic routing, tool federation, and stateful MCP sessions.

Agent-to-Agent (A2A) Gateway

Enables secure, governed communication between AI agents using the A2A protocol for multi-agent orchestration.

Inference Routing

Intelligently routes requests to self-hosted models based on GPU utilization and request priority.

Security and Authentication

Provides JWT, OAuth2, API key management, CORS, CSRF protection, MCP authentication, and external authorization support.

Traffic Management

Supports request routing and matching, header manipulation, rate limiting, retries, gRPC routing, traffic splitting, and direct responses.

Observability

Integrates with OpenTelemetry for metrics, traces, and access logging with a built-in Admin UI and debugging tools.

Guardrails

Applies prompt guards, content filtering, regex filters, moderation policies, and custom webhooks for AI safety.

Cost Controls

Tracks budget and spend limits per user, team, or application with RBAC-based controls on LLM consumption.

Prompt Enrichment

Supports prompt templates and enrichment for standardizing and augmenting requests before routing to LLM providers.

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Semantic Vocabularies 1

JSON-LD contexts and semantic vocabularies used across these APIs.

Agentgateway Context

5 classes · 21 properties

JSON-LD

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

AgentGateway API Rules

5 rules · 3 warnings 2 info

SPECTRAL

JSON Schema 3

Standalone JSON Schema definitions for this provider's data models.

LLMBackend

8 properties

JSON SCHEMA

MCPTarget

6 properties

JSON SCHEMA

Route

5 properties

JSON SCHEMA

JSON Structure 3

JSON Structure definitions describing this provider's data shapes.

Agentgateway Llm Backend Structure

8 properties

JSON STRUCTURE

Agentgateway Mcp Target Structure

6 properties

JSON STRUCTURE

Agentgateway Route Structure

5 properties

JSON STRUCTURE

Examples 3

Example request and response payloads for these APIs.

Agentgateway Llm Backend Example

8 fields

EXAMPLE

Agentgateway Mcp Target Example

6 fields

EXAMPLE

Agentgateway Route Example

5 fields

EXAMPLE

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Agentgateway Domain Security

TLSv1.3

SECURITY

Agentic Access 1

Recommended x-agentic-access execution contracts for AI agents.

Agentgateway Agentic Access

9 operations · 2 acting · 1 human-in-the-loop

9 operations · 2 acting

AGENTIC

Use Cases 6

What developers build with this provider.

Unified LLM Routing

Route requests across multiple LLM providers with a single API, enabling failover, load balancing, and cost optimization without changing client code.

MCP Tool Federation

Aggregate tools from multiple MCP servers behind a single gateway endpoint, enabling agents to discover and invoke tools from any connected MCP server.

Enterprise AI Governance

Apply organization-wide security policies, rate limits, budget controls, and content filters to all AI agent traffic through a centralized gateway.

REST API to MCP Conversion

Convert existing REST APIs into MCP-native tool endpoints that AI agents can discover and invoke through the Model Context Protocol.

Multi-Agent Orchestration

Enable secure agent-to-agent communication using the A2A protocol, allowing specialized agents to delegate tasks to each other through the gateway.

Observability and Debugging

Collect unified telemetry across all AI agent and LLM interactions to monitor cost, latency, and behavior at scale.

Integrations 9

Pre-built integrations with other platforms and tools.

OpenAI

Route to OpenAI GPT models through the AgentGateway LLM backend with model aliasing and budget controls.

Anthropic

Connect to Anthropic Claude models via the unified LLM gateway with failover and load balancing.

Google Gemini

Route traffic to Google Gemini models through the AgentGateway multi-provider backend.

AWS Bedrock

Integrate with AWS Bedrock for managed LLM access via the AgentGateway routing layer.

Azure OpenAI

Route requests to Azure-hosted OpenAI models through the unified gateway API.

Ollama

Connect to locally hosted Ollama models for self-hosted inference routing.

vLLM

Route to vLLM inference servers with GPU utilization-aware routing for optimal performance.

OpenTelemetry

Export metrics, traces, and logs to any OpenTelemetry-compatible observability backend.

Kubernetes Gateway API

Deploy and configure AgentGateway on Kubernetes using the standard Gateway API for dynamic configuration.

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Resources

Get Started 2

Portal, sign-up, and the first successful call

Portal

Portal

GettingStarted

GettingStarted

Documentation 4

Reference material describing how the API behaves

LLM Backend Schema

JSONSchema

MCP Target Schema

JSONSchema

Route Schema

JSONSchema

Documentation

Documentation

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

AgenticAccess

AgenticAccess

LlmsText

LlmsText

Design & Contract 2

Pagination, idempotency, versioning, errors, and events

JSONLD

JSONLD

Vocabulary

Vocabulary

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 1

Status, limits, changes, and where to get help

Support

Support

Company 1

The organization behind the API

Blog

Blog

Source (apis.yml)

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
accessModel:
  pricing: freemium
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Freemium
  confidence: medium
  source:
  - plans
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/agentgateway.png
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
- aid: agentgateway:agentgateway-config-api
  name: AgentGateway Config API
  description: The Config API from AgentGateway — 1 operation(s) for config.
  humanURL: https://agentgateway.dev/
  baseURL: https://agentgateway.dev
  tags:
  - Config
  properties:
  - type: OpenAPI
    url: openapi/agentgateway-config-api-openapi.yml
- aid: agentgateway:agentgateway-debug-api
  name: AgentGateway Debug API
  description: The Debug API from AgentGateway — 2 operation(s) for debug.
  humanURL: https://agentgateway.dev/
  baseURL: https://agentgateway.dev
  tags:
  - Debug
  properties:
  - type: OpenAPI
    url: openapi/agentgateway-debug-api-openapi.yml
- aid: agentgateway:agentgateway-lifecycle-api
  name: AgentGateway Lifecycle API
  description: The Lifecycle API from AgentGateway — 1 operation(s) for lifecycle.
  humanURL: https://agentgateway.dev/
  baseURL: https://agentgateway.dev
  tags:
  - Lifecycle
  properties:
  - type: OpenAPI
    url: openapi/agentgateway-lifecycle-api-openapi.yml
- aid: agentgateway:agentgateway-logging-api
  name: AgentGateway Logging API
  description: The Logging API from AgentGateway — 1 operation(s) for logging.
  humanURL: https://agentgateway.dev/
  baseURL: https://agentgateway.dev
  tags:
  - Logging
  properties:
  - type: OpenAPI
    url: openapi/agentgateway-logging-api-openapi.yml
- aid: agentgateway:agentgateway-memory-api
  name: AgentGateway Memory API
  description: The Memory API from AgentGateway — 1 operation(s) for memory.
  humanURL: https://agentgateway.dev/
  baseURL: https://agentgateway.dev
  tags:
  - Memory
  properties:
  - type: OpenAPI
    url: openapi/agentgateway-memory-api-openapi.yml
- aid: agentgateway:agentgateway-profiling-api
  name: AgentGateway Profiling API
  description: The Profiling API from AgentGateway — 2 operation(s) for profiling.
  humanURL: https://agentgateway.dev/
  baseURL: https://agentgateway.dev
  tags:
  - Profiling
  properties:
  - type: OpenAPI
    url: openapi/agentgateway-profiling-api-openapi.yml
common:
- type: AgenticAccess
  url: agentic-access/agentgateway-agentic-access.yml
- type: DomainSecurity
  url: security/agentgateway-domain-security.yml
- 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.
- type: LlmsText
  url: https://agentgateway.dev/llms.txt
- url: https://agentgateway.dev/blog/index.xml
  type: Blog
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com