RAGFlow MCP Server

by wang-junjian

251 downloads

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Description

# RAGFlow MCP Server RAGFlow API MCP Server，可以查找知识库和聊天。下载 MCP 开发文档和 RAGFlow API 参考： ```bash wget https://modelcontextprotocol.io/llms-full.txt -O docs/mcp-llms-full.txt wget https://github.com/infiniflow/ragflow/raw/refs/heads/main/docs/references/python_api_reference.md -O…

About

Details

Author: wang-junjian
Downloads: 251
Categories: Other

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name RAGFlow MCP Server

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

From the repository

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.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "ragflow mcp server": {
            "ragflow-mcp-server": {
                "command": "uv",
                "args": [
                    "sync"
                ]
            }
        }
    }
}

McpServers

{
    "ragflow-mcp-server": {
        "command": "uv",
        "args": [
            "sync"
        ]
    }
}

RAGFlow MCP Server

RAGFlow API MCP Server，可以查找知识库和聊天。

下载 MCP 开发文档和 RAGFlow API 参考：

wget https://modelcontextprotocol.io/llms-full.txt -O docs/mcp-llms-full.txt
wget https://github.com/infiniflow/ragflow/raw/refs/heads/main/docs/references/python_api_reference.md -O docs/ragflow-python_api_reference.md

Components

Tools

1. list_datasets - 列出所有数据集 - 返回数据集的 ID 和名称

2. create_chat
- 创建一个新的聊天助手
- 输入：
- name: 聊天助手的名称
- dataset_id: 数据集的 ID
- 返回创建的聊天助手的 ID、名称和会话 ID

3. chat
- 与聊天助手进行对话
- 输入：
- session_id: 聊天助手的会话 ID
- question: 提问内容
- 返回聊天助手的回答

Configuration

[TODO: Add configuration details specific to your implementation]

Quickstart

Install

GitHub Copilot

.vscode/mcp.json

{
    "servers": {
        "ragflow-mcp-server": {
            "command": "uvx",
            "args": [
                "ragflow-mcp-server",
                "--api-key=ragflow-dhMzViYzJlMTM1NjExZjBiNWU5MDI0Mm",
                "--base-url=http://172.16.33.66:8060"
            ]
        }
    }
}

Continue

config.yaml

mcpServers:
  - name: RAGFlow Server
    command: uvx
    args:
      - ragflow-mcp-server
      - --api-key
      - ragflow-dhMzViYzJlMTM1NjExZjBiNWU5MDI0Mm
      - --base-url
      - http://172.16.33.66:8060

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json

<details>
<summary>Development/Unpublished Servers Configuration</summary>

  "mcpServers": {

    "ragflow-mcp-server": {

      "command": "uv",

      "args": [

        "--directory",

        "/Users/junjian/GitHub/wang-junjian/ragflow-mcp-server",

        "run",

        "ragflow-mcp-server"

      ]

    }

  }

</details>

<details>
<summary>Published Servers Configuration</summary>

  "mcpServers": {

    "ragflow-mcp-server": {

      "command": "uvx",

      "args": [

        "ragflow-mcp-server"

      ]

    }

  }

</details>

Development

Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:

uv sync

2. Build package distributions:

uv build

This will create source and wheel distributions in the dist/ directory.

3. Publish to PyPI:

uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token: --token or UV_PUBLISH_TOKEN
- Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging
experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector \
  uv --directory /Users/junjian/GitHub/wang-junjian/ragflow-mcp-server \
  run ragflow-mcp-server \
  --api-key ragflow-dhMzViYzJlMTM1NjExZjBiNWU5MDI0Mm \
  --base-url http://172.16.33.66:8060

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

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Description

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

RAGFlow MCP Server

Components

Tools

Configuration

Quickstart

Install

GitHub Copilot

Continue

Claude Desktop

Development

Building and Publishing

Debugging

Install

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