chatGPT_MCP
This project is an MCP stdio server that sends prompts to OpenAI's ChatGPT. It is useful for tasks like summarizing text, analyzing configurations, and reasoning, and is designed to work with LangGraph-based assistants.
π§ Ask ChatGPT - MCP Server (Stdio)
This is a Model Context Protocol (MCP) stdio server that forwards prompts to OpenAIβs ChatGPT (GPT-4o). It is designed to run inside LangGraph-based assistants and enables advanced summarization, analysis, and reasoning by accessing an external LLM.
π 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
π³ 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
π§ͺ 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
π§© 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")
βοΈ MCP Server Config Example
Hereβs 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>"
}
}
}
}
π Explanation
"command": Runs the script with Python
"args": Enables one-shot stdin/stdout mode
"env": Injects your OpenAI key securely
π 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
π¦ Dependencies
Installed during the Docker build:
openai
requests
python-dotenv
π Project Structure
.
βββ Dockerfile # Docker build for the MCP server
βββ server.py # Main stdio server implementation
βββ README.md # You're reading it!
π Security Notes
Never commit .env files or API keys.
Store secrets in secure environment variables or secret managers.