What does RAGFlow MCP Server do?
It acts as a bridge between MCP-compatible AI assistants and the RAGFlow API, allowing you to list datasets and chat with RAGFlow assistants without leaving your editor or chat app.
@wang-junjian
基本信息
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使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"ragflow-mcp-server": {
"command": "uv",
"args": [
"sync"
]
}
}
}聊天助手的名称
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RAGFlow MCP Server is an MCP implementation that exposes RAGFlow’s API as tools for AI assistants. It enables listing datasets, creating chat assistants, and conducting conversations via MCP protocol. Aimed at developers integrating RAGFlow knowledge bases into Copilot, Continue, or Claude Desktop.
Install via uvx ragflow-mcp-server or run from source with uv. Configure with --api-key and --base-url arguments. Example JSON/YAML configs for Copilot, Continue, and Claude Desktop are provided in the README.
It acts as a bridge between MCP-compatible AI assistants and the RAGFlow API, allowing you to list datasets and chat with RAGFlow assistants without leaving your editor or chat app.
Pass `--api-key` (your RAGFlow API key) and `--base-url` (your RAGFlow server address) when launching. Example configs are available for Copilot, Continue, and Claude Desktop.
Python and `uv` (or `uvx` for the published package). The server communicates over stdio via MCP.
All data resides in your RAGFlow instance. The MCP server only sends API requests to your configured `--base-url`.
Transport is MCP over stdio. Authentication is via the RAGFlow API key provided in the `--api-key` argument.

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