Ragdoll AI MCP Server

Ragdoll AI MCP Server

A Model Context Protocol (MCP) server for Ragdoll AI knowledge base queries.

Overview

This MCP server provides a simple interface to query Ragdoll AI knowledge bases through the Model Context Protocol. It allows seamless integration with various LLM client applications including Cursor, Windsurf, and Cline.

Prerequisites

• Bun runtime (v1.2.1 or later)
• Ragdoll AI API key
• Ragdoll AI knowledge base ID

Installation

Clone the repository and install dependencies:

git clone <repository-url>
cd mcp-ragdoll-server
bun install

Configuration

Set up your environment variables:

export RAGDOLL_API_KEY="your-ragdoll-api-key"
export RAGDOLL_KNOWLEDGE_BASE_ID="your-knowledge-base-id"

For persistent configuration, add these to your .bashrc, .zshrc, or create a .env file in the project root.

Running the Server

Start the server:

bun run index.ts

Client Setup

NPX Installation (Recommended)

The simplest way to use this server is via NPX:

npx -y ragdoll-mcp-server

Cursor

To install the Ragdoll MCP server in Cursor IDE:

1. Open Cursor IDE
2. Go to Settings > Extensions > AI Settings
3. Create a file named mcp.json with the following configuration:

{
  "mcpServers": {
    "ragdoll-mcp-server": {
      "command": "npx",
      "args": ["-y", "ragdoll-mcp-server"],
      "env": {
        "RAGDOLL_API_KEY": "your-ragdoll-api-key",
        "RAGDOLL_KNOWLEDGE_BASE_ID": "your-knowledge-base-id"
      }
    }
  }
}

Alternatively, you can run the server locally:

{
  "mcpServers": {
    "ragdoll-mcp-server": {
      "command": "bun",
      "args": ["run", "/path/to/mcp-ragdoll-server/index.ts"],
      "env": {
        "RAGDOLL_API_KEY": "your-ragdoll-api-key",
        "RAGDOLL_KNOWLEDGE_BASE_ID": "your-knowledge-base-id"
      }
    }
  }
}

Windsurf

To install the Ragdoll MCP server in Windsurf IDE:

Create or edit your mcp_config.json file with the following configuration:

{
  "mcpServers": {
    "ragdoll-mcp-server": {
      "command": "npx",
      "args": ["-y", "ragdoll-mcp-server"],
      "env": {
        "RAGDOLL_API_KEY": "your-ragdoll-api-key",
        "RAGDOLL_KNOWLEDGE_BASE_ID": "your-knowledge-base-id"
      }
    }
  }
}

Cline

To install the Ragdoll MCP server in Cline:

Create or edit your cline_mcp_settings.json file with the following configuration:

{
  "mcpServers": {
    "ragdoll-mcp-server": {
      "command": "npx",
      "args": ["-y", "ragdoll-mcp-server"],
      "env": {
        "RAGDOLL_API_KEY": "your-ragdoll-api-key",
        "RAGDOLL_KNOWLEDGE_BASE_ID": "your-knowledge-base-id"
      }
    }
  }
}

Usage

Once connected, you can query your Ragdoll knowledge base with the following parameters:

• query (string, required): The search query to find relevant information
• topK (number, optional): Number of results to return (1-10)
• rerank (boolean, optional): Whether to rerank results

Example usage in your LLM client:

You can ask questions about your knowledge base content.

Development

This project uses the Model Context Protocol SDK. For more information, refer to the MCP documentation.

Support

For issues or questions about this MCP server, please submit an issue on GitHub.

License

MIT