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LazerThings

Twosplit MCP Server

Twosplit MCP Server

An MCP server that leverages multiple Claude instances to provide enhanced responses. It sends the same prompt to two separate instances of Claude and uses a third instance to combine or select the best elements from both responses.

Features

  • Supports multiple Claude models:

    • claude-3-opus-latest

    • claude-3-5-sonnet-latest

    • claude-3-5-haiku-latest

    • claude-3-haiku-20240307

  • Gets single, direct responses from each AI

  • Shows original responses and source attribution

  • Returns optimized final response

Related MCP server: prompte-mcp

Installation

  1. Clone the repository

  2. Install dependencies:

npm install
  1. Build the server:

npm run build

Configuration

The server requires an Anthropic API key to function. Set it as an environment variable:

export ANTHROPIC_API_KEY=your-api-key-here

Usage

The server provides a single tool called twosplit with the following parameters:

  • prompt (required): The prompt to send to Claude

  • model (required): The Claude model to use (must be one of the supported models listed above)

Example tool usage in Claude:

<use_mcp_tool>
<server_name>twosplit</server_name>
<tool_name>twosplit</tool_name>
<arguments>
{
  "prompt": "Write a short story about a robot learning to paint",
  "model": "claude-3-5-sonnet-latest"
}
</arguments>
</use_mcp_tool>

The response will include:

  1. The final optimized response

  2. Original responses from both AIs

  3. Source attribution showing which parts came from which AI

How it Works

  1. The server sends the same prompt to two separate instances of the specified Claude model, requesting a single direct response

  2. A third instance analyzes both responses and either:

    • Selects the single best response if one is clearly superior

    • Creates a new response that combines the best elements from both responses

  3. The final response, original responses, and source attribution are all included in the output

Development

To run the server in watch mode during development:

npm run watch

To inspect the server's capabilities:

npm run inspector
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