gpt2agent

Your codex login → full ChatGPT Plus/Pro account inside any MCP client.

Use your ChatGPT Plus or Pro subscription — every model, every account-tier
feature — inside Claude Code, Codex, and any MCP client.

What it does

gpt2agent exposes 25 MCP tools that forward requests directly to ChatGPT's backend API.
No proxy process. No separate account. No platform API key. Your codex login,
your token, your quota.

If you already have the codex CLI logged in,
setup is zero extra steps — gpt2agent reuses the same ~/.codex/auth.json
bearer and picks up its background-refreshed token automatically.

Works with Claude Code, Codex CLI, and any client that speaks the MCP protocol over stdio.

Install — one line

curl -fsSL https://raw.githubusercontent.com/robotlearning123/gpt2agent/main/install.sh | bash

That command:

1. Installs gpt2agent via pipx (creates an isolated env).
2. Reuses your existing ~/.codex/auth.json if you've run codex login — no separate ChatGPT token paste needed.
3. Detects which MCP clients you have (Claude Code, Codex) and writes the right config snippet for each.
4. Drops the deep-research Claude Code skill into ~/.claude/skills/.

Or step-by-step

# 1. Install the package globally (isolated venv)
pipx install gpt2agent

# 2. Register with all detected MCP clients (Claude Code, Codex)
gpt2agent install                          # auto-detect everything

# Want only one client?
gpt2agent install --client claude-code
gpt2agent install --client codex

# HTTP transport instead of stdio?
gpt2agent install --transport http --http-port 9000

Per-client config

The install subcommand writes the right thing for each:

Both are idempotent and back up the prior file as <name>.bak-gpt2agent.

After running install, restart Claude Code so it re-spawns the subprocess.
Codex picks up the new server on its next invocation automatically.

Manual config (if you'd rather not run install)

Claude Code — add to ~/.claude.json:

{
  "mcpServers": {
    "gpt2agent": {
      "type": "stdio",
      "command": "gpt2agent",
      "args": ["run", "--stdio"]
    }
  }
}

Codex CLI — add to ~/.codex/config.toml:

[mcp_servers.gpt2agent]
command = "gpt2agent"
args = ["run", "--stdio"]

Setup (manual token paste — only if codex isn't available)

gpt2agent setup

Prompts for a ChatGPT session token and saves it to ~/.gpt2agent/token.json.
The codex login flow is preferred when available because codex auto-refreshes
its token; gpt2agent reloads ~/.codex/auth.json on mtime change so long
calls don't 401 mid-flight.

Tools (25)

Chat & reasoning

Image & file management

Code execution

Account introspection

Memory & instructions

Codex (cloud agent)

Architecture

Native Python implementation — no proxy. The server calls
/backend-api/conversation (SSE) directly using curl_cffi for TLS
impersonation. Vendored POW and Turnstile solvers handle the OpenAI Sentinel
challenge. Token is reloaded from disk on each request, so codex's background
refresh propagates transparently. See NOTICES for attribution.

~/.codex/auth.json  (or ~/.gpt2agent/token.json)  ← auto-refreshed by codex
        |
   gpt2agent  (stdio MCP server, token reloaded on each call)
        |
   curl_cffi  →  chatgpt.com /backend-api/{conversation,f/conversation,me,
                                          models, memories, codex, gizmos, ...}
        |
   25 MCP tools  (chat, agent, DR ×2, GPT chat, image gen,
                  code interpreter, canvas, memory r/w,
                  instructions r/w, codex r/w, account introspect)

Configuration

Optional ~/.gpt2agent/config.toml or ./config.toml:

[server]
host = "127.0.0.1"   # loopback only; the HTTP transport is UNAUTHENTICATED
port = 9000

[models]
chat     = "gpt-5-3"        # default for chat tool
agent    = "agent-mode"     # default for agent tool
heavy_dr = "gpt-5-5-pro"    # override slug for deep_research_heavy

Limitations

• Deep Research quota: roughly ~248 heavy requests / monthly cycle on Pro,
  lower on Plus — approximate and account/region-dependent, not a guaranteed number.
• Account-tier features not yet supported: Sora video, Operator/CUA, voice
  sessions. These use HTTP endpoints that return 404 or haven't yet been
  reverse-engineered out of the chatgpt.com web bundle.
• gpt_chat is experimental — gizmo_id payload field verified against
  web traffic but not load-tested across all g-p-* types.
• Requires an active ChatGPT Plus or Pro subscription.

Security & risk — read before you run this

gpt2agent talks to ChatGPT's private backend the way the web app does. That
has real consequences; please understand them before pointing it at your account.

• It impersonates the chatgpt.com web client. It uses curl_cffi TLS
  fingerprint impersonation and vendored Proof-of-Work + Cloudflare Turnstile
  solvers to pass the OpenAI Sentinel challenge. This is very likely against
  the OpenAI Terms of Service, and automated/abnormal traffic can get your
  account rate-limited, challenged, suspended, or banned. Use an account you
  can afford to lose, keep volume human-scale, and don't rely on it for anything
  critical. This is a reverse-engineering / research tool, not an official API.
• The HTTP transport is UNAUTHENTICATED. It proxies your entire account —
  read all conversations, spend Deep Research quota, overwrite custom
  instructions, launch Codex cloud tasks. Anyone who can reach the port controls
  your account. Therefore:
  • Use stdio (the default for gpt2agent install) for local clients like
    Claude Code and Codex. It is not network-exposed.
  • The server binds 127.0.0.1 by default and refuses to start the HTTP
    transport on a non-loopback host unless you explicitly set
    GPT2AGENT_ALLOW_REMOTE=1. Only do that behind your own auth proxy / firewall.
• Your token stays local. It is read from ~/.codex/auth.json (or
  ~/.gpt2agent/token.json, chmod 600) and sent only to chatgpt.com.
  gpt2agent never transmits it anywhere else. Token/secret values are redacted
  from error messages and logs (best-effort).
• PII redaction is limited. Tools that return conversation/memory data strip
  only emails and phone numbers from text — names, addresses, IDs, and the
  full message bodies of get_conversation are returned verbatim. Don't treat
  the output as anonymized.
• GPT2AGENT_RAW_DUMP (debug) writes raw, unredacted SSE/poll traffic —
  including prompts, responses, and resume tokens — to the path you give it.
  Use only for debugging and delete the dumps after.

Found a security issue? See SECURITY.md.

Development

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pytest

Release

Tagged releases are configured to publish to PyPI and create a GitHub Release
with the matching CHANGELOG section:

# bump version
$EDITOR pyproject.toml             # e.g. "0.0.3" → "0.0.4"
$EDITOR CHANGELOG.md               # add ## [0.0.4] - YYYY-MM-DD ...
git commit -am "release: 0.0.4"
git tag v0.0.4
git push origin main --tags        # release workflow fires on the tag

The release workflow (.github/workflows/release.yml) verifies the tag
matches pyproject.toml, runs the test matrix, builds wheel + sdist, publishes
to PyPI via OIDC trusted publishing, and posts a GitHub Release with that
version's CHANGELOG body.

One-time PyPI setup required before the first publish succeeds. PyPI's
OIDC exchange needs a Trusted Publisher registered for this repo (project
gpt2agent, owner robotlearning123, workflow release.yml, environment
pypi) at
pypi.org → Publishing — or a
first manual twine upload to create the project. Until that is done the
release job fails with invalid-publisher and the package is not on PyPI;
the install.sh one-liner falls back to a git+https install in the meantime.

License

MIT. See NOTICES for third-party attributions.

Acknowledgments

• lanqian528/chat2api — POW and Turnstile solver code (MIT)
• basketikun/chatgpt2api — survey of ChatGPT backend API patterns
• 7836246/cursor2api — survey of Cursor API patterns