What are the runtime dependencies?
Node.js (npm) is required. The README does not specify a minimum version, but `npm install` must succeed.
@JQSC
基本情報
mcp-server 合集
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。
MCP 服务工具 is a Model Context Protocol server that provides tool integrations for AI service APIs. It currently supports Hugging Face (text, image, speech, zero‑shot tasks) and Dify (conversational and text generation apps) services. It is aimed at developers who want to use MCP to access these AI models through a unified interface.
Install dependencies with npm install, create a .env file with the required API keys (HUGGINGFACE_API_KEY, DIFY_API_KEY, DIFY_BASE_URL), then start the Dify MCP service using npm run start:dify. For Hugging Face, import and call the tool functions directly in TypeScript, providing the API key and model parameters.
Node.js (npm) is required. The README does not specify a minimum version, but `npm install` must succeed.
For Hugging Face, set `HUGGINGFACE_API_KEY`. For Dify, set `DIFY_API_KEY` and `DIFY_BASE_URL`. These are added in a `.env` file in the project root.
Yes. The README notes that users should be aware of API call limits and associated costs for both Hugging Face and Dify. Exact limits depend on the provider’s plan.
Authentication is handled via API keys supplied in the environment. There is no mention of other auth methods (e.g., OAuth).
The README does not specify the MCP transport (e.g., stdio, SSE). It only shows a start command (`npm run start:dify`) and TypeScript API usage.
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