MCP-Mirror

Ragie Model Context Protocol Server

Community MCP-Mirror
Updated

A Model Context Protocol (MCP) server for Ragie

image

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.

MCP Server · Populars

MCP Server · New

    render-oss

    Render MCP Server

    The Official Render MCP Server

    Community render-oss
    nhevers

    claude-recall

    Long-term memory layer for Clawd & Claude Code that learns and recalls your project context automatically

    Community nhevers
    VienLi

    lark-tools-mcp

    MCP server provides Feishu related operations to AI encoding agents such as cursor 飞书MCP插件,读取文档、发送消息、合同审批、数据处理.....

    Community VienLi
    joeseesun

    🎯 多源内容 → NotebookLM 智能处理器

    Claude Skill: Multi-source content processor for NotebookLM. Supports WeChat articles, web pages, YouTube, PDF, Markdown, search queries → Podcast/PPT/MindMap/Quiz etc.

    Community joeseesun
    avivsinai

    Langfuse MCP Server

    A Model Context Protocol (MCP) server for Langfuse, enabling AI agents to query Langfuse trace data for enhanced debugging and observability

    Community avivsinai