ChatGPT (OpenAI GPT-4o)
About
Integrates with OpenAI's GPT-4o model to provide text analysis, summarization, and generation capabilities through a simple API for scenarios requiring complex processing beyond primary capabilities.
Details
- Author
- automateyournetwork
- Repository
- automateyournetwork/chatGPT_MCP
- GitHub stars
- 2
- Downloads
- 494
- License
- MIT License
- Categories
- Productivity, Developer Tools, Design, Workplace, File Management, AI, Community, Communication, Project Management, Infrastructure
- Tags
- #mobile
Jump to
- Exposes a single tool: ask_chatgpt
- Sends text to GPT-4o for external reasoning
- Supports one-shot stdin/stdout mode
- Deployable via Docker or Python directly
- API key injected securely through environment variables
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
ChatGPT (OpenAI GPT-4o)Command (node, npx, python, etc.)python3Arguments-
Argument 1
server.py -
Argument 2
--oneshot
Environment-
OPENAI_API_KEY
<YOUR_OPENAI_API_KEY>
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Build and run the Docker container with your OPENAI_API_KEY, or run the Python script directly using the --oneshot flag. Configure the server via an mcpServers JSON block, setting the command to python3 server.py --oneshot and providing the API key as an environment variable. The only exposed tool is ask_chatgpt, which takes a content string.
ask_chatgpt
Sends the provided text ('content') to an external ChatGPT (gpt-4o) model for advanced reasoning or summarization. Parameters: content (string) - The text to analyze, summarize, compare, or reason about.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"chatgpt (openai gpt-4o)": {
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
},
"args": [
"server.py",
"--oneshot"
],
"command": "python3"
}
}
}Linux
{
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
},
"args": [
"server.py",
"--oneshot"
],
"command": "python3"
}Macos
{
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
},
"args": [
"server.py",
"--oneshot"
],
"command": "python3"
}Windows
{
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
},
"args": [
"server.py",
"--oneshot"
],
"command": "python3"
}🧠 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
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