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ragie-mcp-server

MCP.Pizza Chef: ragieai

The ragie-mcp-server is a Model Context Protocol server that integrates Ragie's knowledge base retrieval capabilities with AI models. It exposes a 'retrieve' tool allowing models to query and fetch relevant information from Ragie's knowledge base in real time. This server requires Node.js and a Ragie API key, facilitating seamless knowledge retrieval within MCP-enabled environments.

Use This MCP server To

Query Ragie knowledge base for relevant information Integrate Ragie retrieval into AI model workflows Enable real-time knowledge fetching for LLMs Use Ragie data to enrich AI responses Automate information retrieval from Ragie via MCP Combine Ragie retrieval with other MCP tools Support multi-step reasoning with Ragie context Provide scoped access to Ragie knowledge base

README

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Ragie Model Context Protocol Server

A Model Context Protocol (MCP) server that provides access to Ragie's knowledge base retrieval capabilities.

Description

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.

Prerequisites

  • Node.js >= 18
  • A Ragie API key

Installation

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

Command Line Options

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

Cursor Configuration

To use this MCP server with Cursor:

Option 1: Create an MCP configuration file

  1. 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"
      }
    }
  }
}

Option 2: Use a shell script

  1. 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
  1. Give the file execute permissions: chmod +x ragie-mcp.sh

  2. 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.

Claude Desktop Configuration

To use this MCP server with Claude desktop:

  1. 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.

  1. Restart Claude desktop for the changes to take effect.

The Ragie retrieval tool will now be available in your Claude desktop conversations.

Features

Retrieve Tool

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 information
  • topK (number, optional, default: 8): The maximum number of results to return
  • rerank (boolean, optional, default: true): Whether to try and find only the most relevant information
  • recencyBias (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

Development

This project is written in TypeScript and uses the following main dependencies:

  • @modelcontextprotocol/sdk: For implementing the MCP server
  • ragie: For interacting with the Ragie API
  • zod: For runtime type validation

Development setup

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

License

MIT License - See LICENSE.txt for details.

ragie-mcp-server FAQ

How do I authenticate the ragie-mcp-server?
You must provide a valid Ragie API key via the RAGIE_API_KEY environment variable.
What Node.js version is required to run ragie-mcp-server?
Node.js version 18 or higher is required.
How does ragie-mcp-server expose its functionality?
It exposes a single 'retrieve' tool for querying the Ragie knowledge base.
Can I customize the tool description?
Yes, you can override the default tool description using the --description or -d command line option.
How does ragie-mcp-server communicate with MCP clients?
It listens on stdio for MCP protocol messages to interact with clients.
Is ragie-mcp-server compatible with multiple LLM providers?
Yes, it is provider-agnostic and works with OpenAI, Claude, Gemini, and others.
How do I install and run ragie-mcp-server?
Use npx with your Ragie API key: RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server.
Can ragie-mcp-server be integrated into existing MCP workflows?
Yes, it can be combined with other MCP servers and clients for complex workflows.