What is the Twosplit MCP Server?

The Twosplit MCP Server is an innovative tool available on the UBOS Asset Marketplace designed to enhance the output of Claude, Anthropic’s AI model, by leveraging multiple Claude instances for optimized responses.

How does the Twosplit MCP Server work?

The server sends the same prompt to two separate instances of Claude. A third instance then analyzes both responses and either selects the best one or combines elements from both to create a superior final response.

What Claude models are supported by the Twosplit MCP Server?

The server supports a variety of Claude models, including claude-3-opus-latest, claude-3-5-sonnet-latest, and claude-3-5-haiku-latest.

What are the benefits of using the Twosplit MCP Server?

The Twosplit MCP Server improves the quality, depth, and reliability of AI-generated content. It enhances content creation, research, customer service, and code generation processes.

How do I install the Twosplit MCP Server?

1. Clone the repository.
2. Install dependencies using npm install.
3. Build the server using npm run build.
4. Set the Anthropic API key as an environment variable.

How do I use the Twosplit MCP Server?

The server provides a twosplit tool with prompt and model parameters. Use it within Claude by providing the prompt and specifying the Claude model to use.

What is UBOS?

UBOS is a full-stack AI Agent Development Platform focused on bringing AI Agents to every business department. It helps orchestrate AI Agents, connect them with enterprise data, and build custom AI Agents and Multi-Agent Systems.

How does the Twosplit MCP Server integrate with UBOS?

The Twosplit MCP Server is available on the UBOS Asset Marketplace, providing a valuable tool for users of the UBOS platform to enhance their AI capabilities.

Can I contribute to the development of the Twosplit MCP Server?

Yes, developers are encouraged to contribute. Use npm run watch to run the server in watch mode during development and npm run inspector to inspect the server’s capabilities.