What are the prerequisites?
Python 3.8+ and a Poe API key, obtainable from [https://poe.com/api_key](https://poe.com/api_key).
@Anansitrading
基本信息
A lightweight MCP server implementation for accessing OpenAI's o3 model via Poe API
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"po3_MCP": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
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。
A lightweight Model Context Protocol (MCP) server that provides access to OpenAI's o3 model and other models via Poe's API. It is designed for developers who want to integrate Poe's AI capabilities into any MCP‑compatible application.
Install prerequisites (Python 3.8+ and a Poe API key), clone the repository, create a virtual environment, install dependencies, set the POE_API_KEY in a .env file, then run python poe_o3_mcp_server.py. The server listens on standard input/output and exposes two tools: o3_query (sends queries to Poe models, defaulting to “o3”) and ping (returns “pong”). Model selection is done by adding a command‑line‑style flag to the prompt (e.g., --Claude-3.5-Sonnet).
ping toolPython 3.8+ and a Poe API key, obtainable from [https://poe.com/api_key](https://poe.com/api_key).
Add a flag like `--Claude-3.5-Sonnet` anywhere in the prompt (beginning, middle, or end). The flag is automatically removed before sending the message. If no flag is given, the server defaults to the “o3” model.
The server provides two tools: `o3_query` (accepts a `message` parameter) and `ping` (no parameters, returns “pong”).
After installation, execute `python poe_o3_mcp_server.py` from the project directory. The server reads MCP messages from standard input and writes responses to standard output.
Queries are sent to Poe’s API using the API key set in the `POE_API_KEY` environment variable. No local data storage is described. The server communicates via stdin/stdout (stdio transport).

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