A Model Context Protocol (MCP) server that provides access to Ragie's knowledge base retrieval capabilities.
This server implements the Model Context Protocol to enable AI models to retrieve information from a Ragie knowledge base. It provides a single tool called "retrieve" that allows querying the knowledge base for relevant information.
- Node.js >= 18
- A Ragie API key
The server requires the following environment variable:
RAGIE_API_KEY
(required): Your Ragie API authentication key
The server will start and listen on stdio for MCP protocol messages.
Install and run the server with npx:
RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server
The server supports the following command line options:
--description, -d <text>
: Override the default tool description with custom text--partition, -p <id>
: Specify the Ragie partition ID to query
Examples:
# With custom description
RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server --description "Search the company knowledge base for information"
# With partition specified
RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server --partition your_partition_id
# Using both options
RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server --description "Search the company knowledge base" --partition your_partition_id
To use this MCP server with Cursor:
- Save a file called
mcp.json
- For tools specific to a project, create a
.cursor/mcp.json
file in your project directory. This allows you to define MCP servers that are only available within that specific project. - For tools that you want to use across all projects, create a
~/.cursor/mcp.json
file in your home directory. This makes MCP servers available in all your Cursor workspaces.
Example mcp.json
:
{
"mcpServers": {
"ragie": {
"command": "npx",
"args": [
"-y",
"@ragieai/mcp-server",
"--partition",
"optional_partition_id"
],
"env": {
"RAGIE_API_KEY": "your_api_key"
}
}
}
}
- Save a file called
ragie-mcp.sh
on your system:
#!/usr/bin/env bash
export RAGIE_API_KEY="your_api_key"
npx -y @ragieai/mcp-server --partition optional_partition_id
-
Give the file execute permissions:
chmod +x ragie-mcp.sh
-
Add the MCP server script by going to Settings -> Cursor Settings -> MCP Servers in the Cursor UI.
Replace your_api_key
with your actual Ragie API key and optionally set the partition ID if needed.
To use this MCP server with Claude desktop:
- Create the MCP config file
claude_desktop_config.json
:
- For MacOS: Use
~/Library/Application Support/Claude/claude_desktop_config.json
- For Windows: Use
%APPDATA%/Claude/claude_desktop_config.json
Example claude_desktop_config.json
:
{
"mcpServers": {
"ragie": {
"command": "npx",
"args": [
"-y",
"@ragieai/mcp-server",
"--partition",
"optional_partition_id"
],
"env": {
"RAGIE_API_KEY": "your_api_key"
}
}
}
}
Replace your_api_key
with your actual Ragie API key and optionally set the partition ID if needed.
- Restart Claude desktop for the changes to take effect.
The Ragie retrieval tool will now be available in your Claude desktop conversations.
The server provides a retrieve
tool that can be used to search the knowledge base. It accepts the following parameters:
query
(string): The search query to find relevant informationtopK
(number, optional, default: 8): The maximum number of results to returnrerank
(boolean, optional, default: true): Whether to try and find only the most relevant informationrecencyBias
(boolean, optional, default: false): Whether to favor results towards more recent information
The tool returns:
- An array of content chunks containing matching text from the knowledge base
This project is written in TypeScript and uses the following main dependencies:
@modelcontextprotocol/sdk
: For implementing the MCP serverragie
: For interacting with the Ragie APIzod
: For runtime type validation
Running the server in dev mode:
RAGIE_API_KEY=your_api_key npm run dev -- --partition optional_partition_id
Building the project:
npm run build
MIT License - See LICENSE.txt for details.