Agent Gateway in 60 Seconds: Governed LLM Traffic with TrustGate

NeuralTrust has released TrustGate, an open-source, security-first Agent Gateway written in Go that sits between applications and LLM APIs or MCP tool servers. It provides centralized policy enforcement, multi-provider routing, and MCP aggregation through separate Admin, Proxy, and MCP planes, allowing developers to govern LLM traffic without rewriting clients. The gateway supports rate limiting, token limits, semantic caching, and CORS, and can be set up in under a minute using a provided script.

Most teams start with a direct OpenAI or Anthropic SDK call. That works until you have three apps, two providers, and a security review asking who can call which model, at what rate, with what audit trail. An AI / Agent Gateway sits between your apps and agents and every upstream model or tool. One place for routing, policy, and observability — without rewriting clients. TrustGate is NeuralTrust’s open-source, security-first Agent Gateway Go . It fronts LLM APIs and MCP tool servers behind Admin / Proxy / MCP planes, so you change a base URL and two headers instead of scattering keys and rate limits across services. | Plane | Port | Job | |---|---|---| Admin | :8080 | Gateways, registries, consumers, auth, policies | Proxy | :8081 | OpenAI-compatible LLM traffic + plugins | MCP | :8082 | Aggregated Model Context Protocol endpoint for agents e.g. Cursor | Policies rate limit, token rate limit, request size, semantic cache, CORS run in the data path before traffic hits providers. Requires Docker and git . From a clean machine: curl -fsSL https://raw.githubusercontent.com/NeuralTrust/TrustGate/main/scripts/install.sh | bash Or, if you prefer the explicit path: git clone https://github.com/NeuralTrust/TrustGate.git && cd TrustGate cp .env.example .env make up Health checks: curl localhost:8080/healthz Admin curl localhost:8081/healthz Proxy curl localhost:8082/healthz MCP With TrustGate up and OPENAI API KEY set, the repo ships a script that creates a demo gateway, registers OpenAI, mints a consumer key, and sends a chat completion: export OPENAI API KEY="sk-..." ./examples/curl-first-request/first-request.sh From an app, keep the OpenAI SDK — point it at the proxy: python from openai import OpenAI import os client = OpenAI base url="http://localhost:8081/my-app", /{consumer slug} api key="unused", provider key lives in the gateway registry default headers={ "X-AG-Gateway-Slug": "demo", "X-AG-API-Key": os.environ "CONSUMER API KEY" , }, print client.chat.completions.create model="gpt-4o-mini", messages= {"role": "user", "content": "Hello through TrustGate"} , .choices 0 .message.content Full example: examples/openai-sdk/ https://github.com/NeuralTrust/TrustGate/tree/main/examples/openai-sdk . Agents shouldn’t each hold a private mesh of tool servers. TrustGate’s MCP plane :8082 aggregates registered MCP targets behind one endpoint with the same tenancy and policy model. Cursor setup notes live in examples/mcp-cursor/ https://github.com/NeuralTrust/TrustGate/tree/main/examples/mcp-cursor . Choose a gateway when you need central policy who / what / how fast , multi-provider routing with fallback , and increasingly MCP aggregation for agents — not only request logs. If you mainly want a thin multi-provider proxy, LiteLLM is a strong developer default. If you mainly want analytics, Helicone leads with observability. TrustGate’s wedge is governance and security in the data path , including MCP. Docs: docs.neuraltrust.ai https://docs.neuraltrust.ai · Repo: github.com/NeuralTrust/TrustGate https://github.com/NeuralTrust/TrustGate If this was useful, the repo is here — stars help others find it. Disclosure: TrustGate / NeuralTrust DevRel.