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.
The server requires the following environment variable:
RAGIE_API_KEY
(required): Your Ragie API authentication keyThe 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 queryExamples:
# 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:
mcp.json
.cursor/mcp.json
file in your project directory. This allows you to define MCP servers that are only available within that specific project.~/.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"
}
}
}
}
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:
claude_desktop_config.json
:~/Library/Application Support/Claude/claude_desktop_config.json
%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.
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 informationThe tool returns:
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 validationRunning 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.
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