Confidential guide on numerology and astrology, based of GG33 Public information

chatGPT_MCP
An MCP Server for chatGPT Chat Completions
3 years
Works with Finder
1
Github Watches
0
Github Forks
2
Github Stars
🧠 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.
相关推荐
Converts Figma frames into front-end code for various mobile frameworks.
Advanced software engineer GPT that excels through nailing the basics.
Take an adjectivised noun, and create images making it progressively more adjective!
Siri Shortcut Finder – your go-to place for discovering amazing Siri Shortcuts with ease
I find academic articles and books for research and literature reviews.
Discover the most comprehensive and up-to-date collection of MCP servers in the market. This repository serves as a centralized hub, offering an extensive catalog of open-source and proprietary MCP servers, complete with features, documentation links, and contributors.
Micropython I2C-based manipulation of the MCP series GPIO expander, derived from Adafruit_MCP230xx
Bridge between Ollama and MCP servers, enabling local LLMs to use Model Context Protocol tools
🧑🚀 全世界最好的LLM资料总结(Agent框架、辅助编程、数据处理、模型训练、模型推理、o1 模型、MCP、小语言模型、视觉语言模型) | Summary of the world's best LLM resources.
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more.
Reviews

user_3nlUxrYa
ChatGPT_MCP by automateyournetwork is an exceptional tool for network automation enthusiasts. The integration with GitHub ensures easy access and collaboration. With its seamless interface and detailed documentation, tasks that once took hours can now be completed in minutes. Highly recommended for anyone looking to streamline their network management processes! Check it out at: https://github.com/automateyournetwork/chatGPT_MCP.