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.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles AgentGateway the way a machine reads it — 49 machine-readable artifacts across 7 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — AgentGateway scores 52.9/100 (developing), with a separate agent-readiness read of 39/100 (agent aware). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile AgentGateway
Each block below is one kind of artifact we hold for AgentGateway. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 7
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
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.
Scroll within the panel for all 7 ·
Open Collections 1
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
AgentGateway Admin / Debug API
OPEN COLLECTIONPricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Agentgateway Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Agentgateway Finops
FINOPSFeatures 10
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
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.
Scroll within the panel for all 10 ·
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Agentgateway Context
JSON-LDSpectral Rules 1
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
AgentGateway API Rules
SPECTRALJSON Schema 3
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
JSON Structure 3
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
Agentgateway Llm Backend Structure
JSON STRUCTUREAgentgateway Mcp Target Structure
JSON STRUCTUREAgentgateway Route Structure
JSON STRUCTUREExamples 3
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Agentgateway Route Example
EXAMPLESecurity Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 6
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
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 tell you where this provider already fits in a stack.
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.
Scroll within the panel for all 9 ·
Resources
Every other property we hold for AgentGateway — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 2
Portal, sign-up, and the first successful call
Documentation 4
Reference material describing how the API behaves
Agent Surfaces 2
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 2
Pagination, idempotency, versioning, errors, and events
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Company 1
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/agentgateway · machine-readable index on apis.io