ragflow-knowledge-mcp-server

@lumerix7

About ragflow-knowledge-mcp-server

A simple MCP server of knowledge base for RAGFlow.

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "ragflow-knowledge-mcp-server": {
      "command": "python",
      "args": [
        "-m",
        "ragflow_knowledge_mcp_server",
        "--config=/path/to/config.yaml"
      ]
    }
  }
}

Tools

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Overview

What is ragflow-knowledge-mcp-server?

An MCP (Model Context Protocol) server that provides a knowledge base interface for RAGFlow, enabling AI assistants to search and retrieve knowledge from configured datasets. It is intended for developers integrating RAGFlow knowledge bases with MCP-compatible clients.

How to use ragflow-knowledge-mcp-server?

Install via pip (pip install ragflow-knowledge-mcp-server) or from source. Configure via a config.yaml file specifying the RAGFlow API base URL, API key, and dataset definitions. Run with ragflow-knowledge-mcp-server --config=/path/to/config.yaml, using Python or uv, or through Docker/Docker Compose. The server supports both stdio and SSE transports.

Key features of ragflow-knowledge-mcp-server

Dynamic knowledge base searching tools configured per dataset.
List knowledge bases (optional, disabled by default).
Get information of a specific knowledge base (optional, disabled by default).
Configurable via YAML file and environment variables.
Supports both stdio and SSE transports.
Compatible with RAGFlow versions 0.17.2 and 0.18.0.
Logging via simp-logger with file and console output.

Use cases of ragflow-knowledge-mcp-server

Integrate RAGFlow knowledge bases with MCP-compatible AI assistants.
Enable dynamic search of specific knowledge datasets during AI interactions.
List and inspect available knowledge bases for management purposes.
Retrieve metadata about a particular knowledge base.

FAQ from ragflow-knowledge-mcp-server

What RAGFlow versions does this server support?

It supports RAGFlow versions 0.17.2 and 0.18.0.

How do I configure the server?

Configuration is done via a YAML file (default config.yaml) or environment variables. Required settings include default-base-url and default-api-key, plus dataset definitions.

Does the server support SSE transport?

Yes, SSE transport is supported (the default is stdio). Set transport: sse in the config and optionally configure sse-port.

Can I list all knowledge bases?

Yes, the list_knowledge_bases tool is available but disabled by default. Enable it by setting list-bases-enabled: true in the config.

What authentication is used?

The server uses an API key (api-key) to authenticate with the RAGFlow instance. This can be set globally or per dataset.

Frequently asked questions

What RAGFlow versions does this server support?

It supports RAGFlow versions 0.17.2 and 0.18.0.

How do I configure the server?

Configuration is done via a YAML file (default `config.yaml`) or environment variables. Required settings include `default-base-url` and `default-api-key`, plus dataset definitions.

Does the server support SSE transport?

Yes, SSE transport is supported (the default is stdio). Set `transport: sse` in the config and optionally configure `sse-port`.

Can I list all knowledge bases?

Yes, the `list_knowledge_bases` tool is available but disabled by default. Enable it by setting `list-bases-enabled: true` in the config.

What authentication is used?

The server uses an API key (`api-key`) to authenticate with the RAGFlow instance. This can be set globally or per dataset.

Comments

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