Connect GPT to All Models with OpenRouter

فارسی · Agent instructions · Remote deployment · Security

Use ChatGPT as an orchestrator for other AI models. A user can say “ask Gemini,” “review this with GLM,” “send this task to Kimi,” or “compare Claude and Qwen.” ChatGPT calls an MCP tool, this project routes the request through OpenRouter, and the answer returns to the same conversation with the actual model_used value.

Supported friendly aliases include Gemini, Gemini Flash, GLM, Kimi, Claude, DeepSeek, and Qwen. Exact OpenRouter model slugs work too, and other short names can be resolved against OpenRouter's live model catalog.

This project does not turn one model into another. ChatGPT remains the host and orchestrator; OpenRouter provides access to external models that produce delegated answers. Every delegated request may incur OpenRouter charges.

Architecture

flowchart LR
    U["User in ChatGPT"] --> O["ChatGPT orchestrator"]
    O --> T["ngrok HTTPS tunnel"]
    T --> M["OAuth-protected MCP model router"]
    I["Auth0"] -->|"signed access token / JWKS"| M
    M --> G["Private OpenRouter gateway"]
    G --> R["OpenRouter API"]
    R --> A["Gemini / GLM / Kimi / Claude / Qwen / others"]
    A --> O

The project keeps the credential boundary explicit:

1. server.py — a credential-holding HTTP gateway. It binds to 127.0.0.1:3188 by default and talks to OpenRouter.
2. mcp-server.mjs — a stdio MCP server with three tools. It calls the private gateway and never needs to expose the OpenRouter key to ChatGPT.
3. remote-mcp-server.mjs — the optional ChatGPT-web transport. It binds only to loopback, validates Auth0 OAuth access tokens, and exposes /mcp for an HTTPS tunnel such as ngrok.

Features

• Delegate one task to any OpenRouter model.
• Compare two to four models in parallel.
• Resolve aliases from the live catalog, with optional pinned model overrides.
• Return model_requested, model_resolved, and confirmed model_used.
• Keep the OpenRouter key outside ChatGPT and MCP tool responses.
• Use locally through stdio, through an existing local Mac MCP bridge, or from ChatGPT web through a protected HTTPS MCP endpoint.
• Zero third-party Python dependencies; Node is used only for MCP.

Requirements

• Python 3.10 or newer
• Node.js 20 or newer
• An OpenRouter API key with suitable limits
• For ChatGPT web: an HTTPS endpoint and a supported ChatGPT plan/workspace configuration for custom apps/MCP

Quick start

git clone https://github.com/Erfouni/connect-gpt-to-all-models-with-openrouter.git
cd connect-gpt-to-all-models-with-openrouter
cp .env.example .env
npm install

Edit .env and add your own key:

OPENROUTER_API_KEY=

Never paste that key into ChatGPT, a GPT instruction, an MCP configuration, a tunnel command, a screenshot, or a Git commit.

Start the private gateway:

python3 server.py

In another terminal:

curl http://127.0.0.1:3188/health
npm test

An optional paid API smoke test:

curl -X POST http://127.0.0.1:3188/run \
  -H 'Content-Type: application/json' \
  -d '{"model":"gemini","prompt":"Reply with exactly: ROUTER_OK","max_tokens":64}'

Operating modes

1. Local stdio MCP

Use this with an MCP client running on the same computer. Copy examples/mcp-client-config.json, replace the absolute path, and add it to your client's MCP configuration. Keep the gateway running, then the client starts mcp-server.mjs over stdio.

npm run start:mcp

See Local setup.

2. Existing Mac MCP bridge

If ChatGPT already has access to a trusted Mac MCP that includes an HTTP-fetch tool, it can call the loopback gateway directly from that Mac:

POST http://127.0.0.1:3188/run

This keeps both the key and gateway private. Use the bridge-mode instructions in Agent instructions. Do not expose a general filesystem or shell MCP publicly just to reach this gateway.

3. Protected server / ChatGPT web

For ChatGPT web, configure the Auth0 and public URL fields in .env, then start the authenticated Streamable HTTP server:

npm run start:mcp:http

It listens only on loopback by default; the MCP path is:

http://127.0.0.1:3200/mcp

The server validates the token signature through Auth0 JWKS, plus issuer, audience, expiration, required scopes, and an optional client-ID allowlist. It also publishes OAuth protected-resource metadata for ChatGPT discovery. Tunnel only port 3200; never tunnel the private gateway on 3188.

After configuring your own ngrok reserved domain and local ngrok authtoken, run:

./scripts/start-secure-ngrok.sh

The URL registered in ChatGPT must be the same HTTPS resource URL configured as PUBLIC_MCP_URL and AUTH0_AUDIENCE, for example:

https://mcp.example.com/mcp

It is not a local path such as /Users/name/project/start.sh. No ngrok domain, authtoken, MCP token, API key, or personal path is included in this repository. Create your own Auth0 application/API, ngrok tunnel, and credentials. See Remote deployment before exposing anything. A static API key or ngrok browser login is not a substitute for the MCP OAuth flow expected by ChatGPT.

ChatGPT / Custom GPT setup

1. Get the local or protected remote MCP mode working first.
2. In ChatGPT, connect the custom app/MCP endpoint allowed by your plan or workspace. For server mode, enter https://YOUR_DOMAIN/mcp and select OAuth authentication.
3. Create a Custom GPT and enable the connected app, if that option is available for your account/workspace.
4. Paste the provided instructions into the GPT instructions field.
5. Save it privately and test: “Ask Gemini to reply with MODEL_OK.”
6. Confirm that the response includes a real model_used value.

On ChatGPT web, a saved GPT can also be brought into an existing conversation with @GPT_NAME, subject to current ChatGPT availability and workspace policy.

MCP tools

Tool	Purpose
openrouter_list_models	Search the current OpenRouter catalog
openrouter_run_model	Delegate one prompt to a requested model
openrouter_compare_models	Run the same prompt with 2–4 models

Gateway API

Endpoint	Purpose
GET /health	Readiness and key-configuration status
GET /models?search=...	Search models
POST /run	Run one model
POST /compare	Compare models in parallel
POST /refresh-models	Refresh the cached catalog

Example request:

{
  "model": "kimi",
  "prompt": "Review the relevant conversation and list the three biggest risks.",
  "reasoning_effort": "high",
  "max_tokens": 4096
}

Exact slugs such as provider/model-name are passed through unchanged. Alias defaults can be pinned in .env; otherwise the newest matching live catalog entry is selected.

Security essentials

• .env is ignored by Git. Only .env.example belongs in the repository.
• The gateway refuses a non-loopback bind unless OPENROUTER_AGENT_TOKEN is set.
• The authenticated remote MCP also refuses a non-loopback bind. ngrok connects locally to it and provides public TLS.
• Do not expose port 3188 to the internet. Expose only port 3200 through the tunnel after OAuth has been configured.
• Do not publish a broad shell/filesystem MCP alongside this model router.
• Send external models only the context required for the delegated task.
• Set OpenRouter budget/rate limits and remember that /compare creates several independent billed requests.
• Rotate any credential that has ever appeared in chat, logs, screenshots, or Git history.

Read the full security policy and deployment checklist.

Automatic startup on macOS

After creating .env, install the generated LaunchAgent for the private Python gateway:

chmod +x scripts/*.sh
./scripts/install-macos-launchagent.sh

The installer computes paths locally. No username or personal path is stored in the repository.

Tests

npm test
python3 -m unittest discover -s tests -p 'test_*.py'
python3 -m py_compile server.py

These tests do not call a paid model.

License

MIT