Frequently Asked Questions (FAQ) about MCP Server for Cappt

Q: What is the MCP Server for Cappt?

A: The MCP Server for Cappt is a Model Context Protocol server designed for generating outlines and presentations using Cappt.cc. It allows users to input outlines or content and receive structured presentations with editable URLs and gallery options.

Q: How do I install the MCP Server for Cappt?

A: The recommended method is to use uv. Navigate to the repository directory, create a virtual environment, activate it, and then run uv install -e ..

Q: How do I configure the MCP Server for Cappt with Claude Desktop?

A: Add a configuration block to your claude_desktop_config.json file, specifying the command as uv, the arguments including the path to your repository and run mcp-server-cappt, and setting the CAPPT_TOKEN environment variable.

Q: What is the Model Context Protocol (MCP)?

A: MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs), ensuring efficient and relevant AI interactions.

Q: What are the main features of the MCP Server for Cappt?

A: The main features include generating presentations from outlines, generating outlines from user inputs, and providing detailed information about the generated content, such as record IDs, status, total pages, editor URLs, titles, thumbnails, and galleries.

Q: How do I debug the MCP Server for Cappt?

A: Use the MCP inspector tool. Ensure the package is installed with uv, then run npx @modelcontextprotocol/inspector uv run mcp-server-cappt --cappt-token YOUR_CAPPT_TOKEN.

Q: What license is the MCP Server for Cappt released under?

A: The MCP Server for Cappt is licensed under the MIT License, allowing for free use, modification, and distribution, subject to the terms and conditions outlined in the LICENSE file.

Q: How does the UBOS platform enhance the use of the MCP Server for Cappt?

A: UBOS provides a comprehensive environment for AI agent development and orchestration, allowing businesses to seamlessly manage and coordinate AI agents, connect them with enterprise data, build custom AI agents, and develop multi-agent systems.