ragflow-knowledge-mcp-server
About
A simple MCP server of knowledge base for RAGFlow.
Details
- Author
- lumerix7
- Downloads
- 314
- Categories
- Knowledge Base
Jump to
- 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.
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-knowledge-mcp-serverCommand (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
From the repository
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.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"ragflow-knowledge-mcp-server": {
"ragflow-knowledge-mcp-server": {
"command": "python",
"args": [
"-m",
"ragflow_knowledge_mcp_server",
"--config=/path/to/config.yaml"
]
}
}
}
}McpServers
{
"ragflow-knowledge-mcp-server": {
"command": "python",
"args": [
"-m",
"ragflow_knowledge_mcp_server",
"--config=/path/to/config.yaml"
]
}
}ragflow-knowledge-mcp-server
A simple MCP server of knowledge base for RAGFlow.Supported RAGFlow versions:
- 0.17.2
- 0.18.0
See also infiniflow/ragflow/blob/main/mcp/server/server.py
1. Available tools
1. Dynamic knowledge base searching tools
Enable dynamic knowledge base searching tools inconfig.yaml, see also Server configurations:
datasets:
- dataset-id: 00000000000000000000000000000000
search-tool-name: search_xxx_knowledge
#search-tool-description: "Search knowledge about XXX(中文说明)."
#search-tool-result: simple
search-tool-description: "Search knowledge about XXX(中文说明). Results in JSON format, knowledge in the 'content' property."
search-tool-result: json
2. list_knowledge_bases (default disabled)
Enable list_knowledge_bases tool in config.yaml:
list-bases-enabled: true
- Default description:
List knowledge bases.
- Input properties:
page, str: The page number to list the bases for, optional, defaults to 1.
limit, str: The maximum number of knowledge bases to list, optional, defaults to 20.
timeout, int: Dynamic timeout parameter, enabled by timeout-param-enabled, optional, defaults to 60 seconds.
3. get_knowledge_base_info (default disabled)
Enable get_knowledge_base_info tool in config.yaml:
get-base-enabled: true
- Default description:
Get information of the specified knowledge base ID, results including the knowledge base name, description, and other information.
- Input properties:
knowledge_base_id, str: The ID of the knowledge base to query.
* timeout, int: Dynamic timeout parameter, enabled by timeout-param-enabled, optional, defaults to 60 seconds.
2. Install and run
2.1. Install using pip
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