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What is the Prompt Engineer MCP Server?

The Prompt Engineer MCP Server is a tool that rewrites coding prompts for optimal results with AI IDEs like Cursor AI, using Claude by Anthropic.

How does the Prompt Engineer MCP Server work?

It uses Claude 3 Sonnet to intelligently rewrite prompts, adding structure, context, language-specific considerations, and optimizing for AI IDE understanding.

What are the benefits of using the Prompt Engineer MCP Server?

It enhances code generation, streamlines debugging, automates code refactoring, accelerates learning, and integrates seamlessly with AI IDEs.

How do I install the Prompt Engineer MCP Server?

You can install it using npm with the command npm install.

How do I configure the server with my Anthropic API key?

Set the ANTHROPIC_API_KEY environment variable: export ANTHROPIC_API_KEY=your_anthropic_api_key.

How do I run the server?

Run the server using npm start or with MCP Inspector using npx @modelcontextprotocol/inspector npm start.

What is the rewrite_coding_prompt tool?

This tool takes a raw prompt and rewrites it for optimal results with AI IDEs.

What parameters does the rewrite_coding_prompt tool require?

It requires the prompt (the raw user’s prompt) and the language (the programming language of the code).

How does the language-aware feature work?

The server customizes prompts based on the target programming language, considering syntax and semantics for better results.

What is the license of the Prompt Engineer MCP Server?

It is licensed under the MIT License, allowing you to use, modify, and distribute the software.

How does the Prompt Engineer MCP Server integrate with UBOS?

The Prompt Engineer MCP Server can be seamlessly integrated with the UBOS platform to build custom AI Agents tailored to your specific needs, orchestrate AI Agents, connect them with your enterprise data, and build Multi-Agent Systems.

What is an MCP Server?

MCP is an open protocol that standardizes how applications provide context to LLMs. An MCP (Model Context Protocol) server acts as a bridge, allowing AI models to access and interact with external data sources and tools.

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