Skip to main content

A Model Context Protocol server for interacting with ChatGPT on macOS with Korean support

Project description

ChatGPT MCP Server

A Model Context Protocol (MCP) server that enables AI assistants to interact with the ChatGPT desktop app on macOS.

ChatGPT Server MCP server

https://github.com/user-attachments/assets/a30c9b34-cdbe-4c0e-a0b0-33eb5054db5c

Language Support

Supported system languages for response detection:

  • Korean
  • English

If your macOS system language is not listed above, please follow these instructions:

  1. Make sure ChatGPT desktop app is running
  2. Run show_all_button_names.applescript and copy the output to create an issue for language support.

Features

  • Send prompts to ChatGPT from any MCP-compatible AI assistant
  • Built with Python and FastMCP

Note: This server only supports English text input. Non-English characters may not work properly.

Installation

Prerequisites

  • macOS
  • ChatGPT desktop app installed and running
  • Python 3.10+
  • uv package manager

For Claude Code Users

Simply run:

claude mcp add chatgpt-mcp uvx chatgpt-mcp

That's it! You can start using ChatGPT commands in Claude Code.

For Other MCP Clients

Step 1: Install the MCP Server

Option A: Install from PyPI (Recommended)

# Install with uv
uv add chatgpt-mcp

Option B: Manual Installation

# Clone the repository
git clone https://github.com/xncbf/chatgpt-mcp
cd chatgpt-mcp

# Install dependencies with uv
uv sync

Step 2: Configure Your MCP Client

If installed from PyPI, add to your MCP client configuration:

{
  "mcpServers": {
    "chatgpt": {
      "command": "uvx",
      "args": ["chatgpt-mcp"]
    }
  }
}

If manually installed, add to your MCP client configuration:

{
  "mcpServers": {
    "chatgpt": {
      "command": "uv",
      "args": ["run", "chatgpt-mcp"],
      "cwd": "/path/to/chatgpt-mcp"
    }
  }
}

Usage

  1. Open ChatGPT desktop app and make sure it's running
  2. Open your MCP client (Claude Code, etc.)
  3. Use ChatGPT commands in your AI assistant:
    • "Send a message to ChatGPT"

The AI assistant will automatically use the appropriate MCP tools to interact with ChatGPT.

Available Tools

ask_chatgpt

Send a prompt to ChatGPT and receive the response.

ask_chatgpt(prompt="Hello, ChatGPT!")

get_chatgpt_response

Get the latest response from ChatGPT after sending a message.

get_chatgpt_response()

new_chatgpt_chat

Start a new chat conversation in ChatGPT.

new_chatgpt_chat()

Development

Local Testing

To test the MCP server locally during development:

  1. Install in editable mode

    uv pip install -e .
    
  2. Test with MCP Inspector

    npx @modelcontextprotocol/inspector chatgpt-mcp
    

The editable installation creates a chatgpt-mcp command that directly references your source code, so any changes you make are immediately reflected without reinstalling.

Running without installation

You can also run the server directly:

PYTHONPATH=. uv run python -m chatgpt_mcp.chatgpt_mcp

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iflow_mcp_chatgpt_mcp-1.2.1.tar.gz (8.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

iflow_mcp_chatgpt_mcp-1.2.1-py3-none-any.whl (10.3 kB view details)

Uploaded Python 3

File details

Details for the file iflow_mcp_chatgpt_mcp-1.2.1.tar.gz.

File metadata

File hashes

Hashes for iflow_mcp_chatgpt_mcp-1.2.1.tar.gz
Algorithm Hash digest
SHA256 e019dfe35aa2b2dc9fee3ffd80c8faf1f6fe2eb937b4e5d26c6134b553c01a91
MD5 4f9e1ed8eb7f780eb2caf4574d530c6e
BLAKE2b-256 fedc5fb7cb3b505f1d100052b9f86662702f6b9af040009c7dff8386d66049b3

See more details on using hashes here.

File details

Details for the file iflow_mcp_chatgpt_mcp-1.2.1-py3-none-any.whl.

File metadata

File hashes

Hashes for iflow_mcp_chatgpt_mcp-1.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 ac0e23451c709b0c5da2cf29e84d14e79e50659a82af4ee5cb9b855daa50f0fe
MD5 d0fccc00150392a68fc0201f29f4a615
BLAKE2b-256 4a964bc2c29c7eab20abdda1fd1b80a0ff852615d4c40cb6d0f3cd068ce99792

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page