Chatgpt

Name: Chatgpt
Author: automateyournetwork

@automateyournetwork

代码仓库

关于 Chatgpt

暂无概览

#chatgpt #mcp-server #ai-assistant

基本信息

分类

AI 与智能体

传输方式

stdio

发布者

automateyournetwork

提交者

John Capobianco

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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.