Twosplit MCP Server
An MCP server that leverages multiple Claude instances to provide enhanced responses by sending the same prompt to two separate instances and using a third to combine or select the best elements.
Tools
twosplit
Get multiple AI perspectives and combine them into the best response
README
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
Installation
- Clone the repository
- Install dependencies:
npm install
- 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 Claudemodel(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:
- The final optimized response
- Original responses from both AIs
- Source attribution showing which parts came from which AI
How it Works
- The server sends the same prompt to two separate instances of the specified Claude model, requesting a single direct response
- 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
- 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
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.