What LLM models does element-plus-mcp support?
It supports DeepSeek (default), OpenAI, Anthropic, and Google Gemini, configurable via environment variables.
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基本信息
element-plush mcp server
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。
element-plus-mcp is an MCP (Model Context Protocol) server that generates Element Plus Vue components on demand using large language models (LLMs). It is designed for developers who want to quickly scaffold Vue components by describing them in natural language, with support for multiple LLM providers and a built-in live preview service.
Configure API keys in a .env file (supports DeepSeek, OpenAI, Anthropic, Gemini). Start the server, then send HTTP requests to the /api/mcp/generate endpoint with a userPrompt and optional llmConfig. For MCP protocol usage, send JSON-RPC calls to /api/mcp-protocol/mcp or use SSE connections at /api/mcp-protocol/sse. Use the /api/mcp/models endpoint to list available models.
It supports DeepSeek (default), OpenAI, Anthropic, and Google Gemini, configurable via environment variables.
The server uses an LRU cache for component descriptions and completions to avoid redundant API calls, but no persistent data storage is mentioned.
You can connect via HTTP JSON-RPC at `/api/mcp-protocol/mcp` or via SSE at `/api/mcp-protocol/sse`. The server also provides a standard HTTP generation endpoint at `/api/mcp/generate`.
The README mentions concurrency control via a task queue to prevent token overruns and rate limits, but no specific limits are given.
No authentication is mentioned in the README; API keys are configured server-side in the `.env` file for LLM providers.

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