What are the runtime dependencies?
Node.js (npm) is required. The README does not specify a minimum version, but `npm install` must succeed.
@JQSC
Basic information
mcp-server 合集
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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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