Openai

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.

PyPI version License: MIT Python 3.10+

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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.

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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:

Client	File	Section
Claude Code	~/.claude.json	mcpServers.gpt2agent (stdio: gpt2agent run --stdio)
Codex CLI	~/.codex/config.toml	[mcp_servers.gpt2agent]

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"]

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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.

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Tools (25)

Chat & reasoning

Tool	What it does
chat	Talk to any model on your account (gpt-5-3 default, override via model=). Pass gpt-5-5-pro, o3-pro, gpt-5-4-thinking, …
agent	Agent Mode — 262K context with autonomous browsing, code execution, tool use
deep_research	Web-augmented research with citations (~30–120 s). Auto-confirms by default
deep_research_heavy	Long-form DR via gpt-5-5-pro + connector (5–30 min, monthly quota). Configurable via [models].heavy_dr
gpt_chat	Talk through one of your private Custom GPTs (g-p-*) — experimental

Image & file management

Tool	What it does
generate_image	Generate images via ChatGPT's built-in DALL-E. Returns download URLs + metadata
get_file_info	Metadata for any ChatGPT file (images, uploads)
get_file_download_url	Temporary download URL for a ChatGPT file (~1h expiry)

Code execution

Tool	What it does
code_interpreter	Run Python in ChatGPT's sandbox. Returns output + any generated charts/images
canvas_execute	Execute code via ChatGPT's Canvas feature (live editing environment)

Account introspection

Tool	What it does
account_status	Plan, country, MFA, feature count, subscription expiry
list_models	All models on your account (slug, max_tokens, reasoning_type, capabilities, enabled_tools)
list_conversations	Recent ChatGPT conversations (PII redacted)
get_conversation	Full message history for a specific conversation (multimodal, code, images)
list_tasks	Scheduled / completed ChatGPT tasks
list_apps	Connected apps + connectors
list_custom_gpts	Your private g-p-* GPTs

Memory & instructions

Tool	What it does
memory_list	List all ChatGPT memory entries (PII redacted)
memory_search	Keyword filter over memories
memory_create_via_chat	Add a memory (model-initiated workaround — POST /memories is 405)
custom_instructions_get	Read your current about_user / about_model
custom_instructions_set	Update them (read-modify-write, preserves unspecified fields)

Codex (cloud agent)

Tool	What it does
list_codex_envs	Codex environments (label, repos, network policy)
list_codex_tasks	Recent Codex tasks + status
codex_task_create	Kick off a new Codex task (resolves env from repo_label)

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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, ...}
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   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)

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Configuration

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

[server]
host = "0.0.0.0"
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

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Limitations

• Deep Research quota: ~248 requests / monthly cycle on Pro; lower on Plus.
• Account-tier features unavailable in 0.0.2: 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.

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Development

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

Release

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

# bump version
$EDITOR pyproject.toml             # e.g. "0.0.2" → "0.0.3"
$EDITOR CHANGELOG.md               # add ## [0.0.3] - YYYY-MM-DD ...
git commit -am "release: 0.0.3"
git tag v0.0.3
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 (no token in secrets — one-time setup at pypi.org/manage/account/publishing), and posts a GitHub Release with that version's CHANGELOG body.

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License

MIT. See NOTICES for third-party attributions.

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Acknowledgments

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