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
基本情報
A lightweight MCP server implementation for accessing OpenAI's o3 model via Poe API
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"po3_MCP": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
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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