Chatgpt Mcp

What is Chatgpt Mcp

chatGPT_MCP is a Model Context Protocol (MCP) server designed to facilitate communication with OpenAI’s ChatGPT (GPT-4o) for advanced reasoning, summarization, and analysis tasks within LangGraph-based assistants.

Use cases

Use cases include summarizing long documents, analyzing configuration files, comparing different options, and performing advanced natural language reasoning tasks.

How to use

To use chatGPT_MCP, build and run the Docker container with your OpenAI API key. You can also test it locally with a one-shot request or integrate it into your LangGraph pipeline using the provided configuration.

Key features

Key features include the ability to send text for analysis, summarization, comparison, and reasoning. It operates in a one-shot mode, allowing for quick interactions with the ChatGPT model.

Where to use

chatGPT_MCP can be used in various fields such as customer support, content creation, data analysis, and any application requiring natural language processing and understanding.

🧠 Ask ChatGPT - MCP Server (Stdio)

This is a Model Context Protocol (MCP) stdio server that forwards prompts to OpenAI’s ChatGPT (GPT-4o). It is designed to run inside LangGraph-based assistants and enables advanced summarization, analysis, and reasoning by accessing an external LLM.

📌 What It Does

This server exposes a single tool:

{
  "name": "ask_chatgpt",
  "description": "Sends the provided text ('content') to an external ChatGPT (gpt-4o) model for advanced reasoning or summarization.",
  "parameters": {
    "type": "object",
    "properties": {
      "content": {
        "type": "string",
        "description": "The text to analyze, summarize, compare, or reason about."
      }
    },
    "required": [
      "content"
    ]
  }
}

Use this when your assistant needs to:

Summarize long documents

Analyze configuration files

Compare options

Perform advanced natural language reasoning

🐳 Docker Usage

Build and run the container:

docker build -t ask-chatgpt-mcp .

docker run -e OPENAI_API_KEY=your-openai-key -i ask-chatgpt-mcp

🧪 Manual Test

Test the server locally using a one-shot request:

echo '{"method":"tools/call","params":{"name":"ask_chatgpt","arguments":{"content":"Summarize this config..."}}}' | \
  OPENAI_API_KEY=your-openai-key python3 server.py --oneshot

🧩 LangGraph Integration

To connect this MCP server to your LangGraph pipeline, configure it like this:

("chatgpt-mcp", ["python3", "server.py", "--oneshot"], "tools/discover", "tools/call")

⚙️ MCP Server Config Example

Here’s how to configure the server using an mcpServers JSON config:

{
  "mcpServers": {
    "chatgpt": {
      "command": "python3",
      "args": [
        "server.py",
        "--oneshot"
      ],
      "env": {
        "OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
      }
    }
  }
}

🔍 Explanation

“command”: Runs the script with Python

“args”: Enables one-shot stdin/stdout mode

“env”: Injects your OpenAI key securely

🌍 Environment Setup

Create a .env file (auto-loaded with python-dotenv) or export the key manually:

OPENAI_API_KEY=your-openai-key

Or:

export OPENAI_API_KEY=your-openai-key

📦 Dependencies

Installed during the Docker build:

openai

requests

python-dotenv

📁 Project Structure

.
├── Dockerfile        # Docker build for the MCP server
├── server.py         # Main stdio server implementation
└── README.md         # You're reading it!

🔐 Security Notes

Never commit .env files or API keys.

Store secrets in secure environment variables or secret managers.