gpt-subagents-subscription
Unofficial MCP server that provides GPT subagent tools using a ChatGPT subscription via OAuth, enabling access to GPT models for orchestrated tasks.
README
gpt-subagents-subscription
An MCP server that exposes GPT "subagent" tools backed by your ChatGPT subscription — using
OpenAI's "Sign in with ChatGPT" OAuth instead of a pay-per-use API key. Sibling to
gpt-subagents-api (which uses an API key), and
it ships the same orchestration patterns system.
Note: Authenticates via OpenAI's "Sign in with ChatGPT" OAuth — the mechanism OpenAI introduced (through Codex CLI) for bringing your ChatGPT subscription to a third-party tool — and calls the ChatGPT backend with the resulting token. Not affiliated with or endorsed by OpenAI. These backend endpoints aren't versioned and can change; if a call starts failing, the stable alternative is the API-key sibling
gpt-subagents-api.
Tools
| Tool | What it does |
|---|---|
ask_gpt |
Ask a GPT model via your ChatGPT subscription. You pick model and write instructions (the system prompt) every call — both required, no defaults. Any valid model id is accepted; known suggestions: gpt-5.4 (general), gpt-5.4-mini (faster/cheaper), gpt-5.5 (deepest reasoning). Optional reasoning_effort (low/medium/high). |
check_usage |
Remaining ChatGPT/Codex subscription quota |
list_patterns / get_pattern |
Orchestration patterns for driving the model well (see below) |
Orchestration patterns
Patterns are reusable playbooks (Markdown in patterns/) that describe how to drive
the expert tools — splitting work, bundling context, calling the expert, verifying its output
against ground truth, and aggregating. They're exposed via list_patterns (catalog) and
get_pattern("<name>") (full text), read from disk at call time (no rebuild to add one), and the
server's instructions nudge the agent to consult them before non-trivial expert work.
| name | what it does |
|---|---|
two-layer-cross-model-expert |
Wrap the GPT expert in verifying Claude subagents so the orchestrator only ever sees parallel, context-cheap, ground-truth-checked conclusions. |
worker-orchestrator |
Fan concrete work out to the GPT worker (ask_gpt with a fast model) through cheap Sonnet wrapper subagents — validated by execution, not a verification gate. |
Both patterns ship a rendered diagram under patterns/html/. See patterns/README.md to add your own.
Setup
Requires Node 18+ and an active ChatGPT subscription.
npm install
npm run build
npm run login # prints a sign-in URL to open; sign in with ChatGPT (one-time)
npm run login runs an OAuth flow on http://localhost:1455/auth/callback and stores tokens at
~/.gpt-subagents-subscription/auth.json (mode 0600, never committed). Run
npm run login -- --logout to clear them.
Register with Claude Code
claude mcp add gpt-subagents-subscription -- node /absolute/path/to/gpt-subagents-subscription/dist/server.js
How it works
npm run login→ PKCE OAuth againstauth.openai.com→ tokens stored locally.- The MCP server reads and auto-refreshes those tokens.
- Tool calls POST to
chatgpt.com/backend-api/codex/responseswithAuthorization: Bearer+ChatGPT-Account-Id, using the Responses API schema.
Security
- Tokens live outside the repo (
~/.gpt-subagents-subscription/) and are gitignored everywhere. - No credentials are committed;
.env.exampleholds only optional model overrides. - This project never reads your existing
~/.codex/auth.json— it mints its own tokens. - Local agent/editor state (
.mempalace/,.claude/,CLAUDE.local.md, IDE folders) is gitignored.
Credits / prior art
The "Sign in with ChatGPT" subscription flow has been documented by the community, e.g. EvanZhouDev/openai-oauth and various write-ups.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.