Chatgpt
@automateyournetwork
About Chatgpt
No overview available yet
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"chatgpt": {
"command": "python3",
"args": [
"server.py",
"--oneshot"
],
"env": {
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>"
}
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Chatgpt?
This MCP (Model Context Protocol) stdio server forwards prompts to OpenAI’s ChatGPT (GPT-4o) for advanced summarization, analysis, and reasoning. It is designed to run inside LangGraph-based assistants.
How to use Chatgpt?
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.
Key features of Chatgpt
- 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
Use cases of Chatgpt
- Summarize long documents
- Analyze configuration files
- Compare multiple options
- Perform advanced natural language reasoning
FAQ from Chatgpt
What tool does this server expose?
It exposes the ask_chatgpt tool, which forwards the provided content to GPT-4o for analysis or summarization.
How do I provide my OpenAI API key?
Set the OPENAI_API_KEY environment variable, either in a .env file (auto‑loaded by python‑dotenv) or by exporting it directly.
Can I test the server locally?
Yes, use the --oneshot flag and send a JSON‑formatted request via echo, as shown in the README manual test example.
How do I integrate Chatgpt with LangGraph?
Configure the server with command python3, args ["server.py", "--oneshot"], and the OPENAI_API_KEY in the environment block of your LangGraph pipeline.
What dependencies does it require?
The server depends on openai, requests, and python-dotenv; these are installed during the Docker build.
Frequently asked questions
What tool does this server expose?
It exposes the `ask_chatgpt` tool, which forwards the provided `content` to GPT-4o for analysis or summarization.
How do I provide my OpenAI API key?
Set the `OPENAI_API_KEY` environment variable, either in a `.env` file (auto‑loaded by python‑dotenv) or by exporting it directly.
Can I test the server locally?
Yes, use the `--oneshot` flag and send a JSON‑formatted request via `echo`, as shown in the README manual test example.
How do I integrate Chatgpt with LangGraph?
Configure the server with command `python3`, args `["server.py", "--oneshot"]`, and the `OPENAI_API_KEY` in the environment block of your LangGraph pipeline.
What dependencies does it require?
The server depends on `openai`, `requests`, and `python-dotenv`; these are installed during the Docker build.
Basic information
More AI & Agents MCP servers
Just Prompt - A lightweight MCP server for LLM providers
dislerjust-prompt is an MCP server that provides a unified interface to top LLM providers (OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama)
XDC AI
XDC AI is a remote MCP server available at https://xdcai.tech.
🔎 GPT Researcher
assafelovicAn autonomous agent that conducts deep research on any data using any LLM providers
Open Multi-Agent Canvas
CopilotKitThe open-source multi-agent chat interface that lets you manage multiple agents in one dynamic conversation and add MCP servers for deep research
1Panel
1Panel-dev🔥 1Panel is a modern, open-source VPS control panel — and the only one with native AI agent support. Run Ollama models, deploy OpenClaw agents, and manage your entire server stack from one clean web interface.
Comments