Frequently Asked Questions (FAQ) about UBOS Asset Marketplace MCP Server for promptz.dev

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

Q: What is the UBOS Asset Marketplace MCP Server for promptz.dev? A: It’s an integration that allows you to access prompts from promptz.dev directly within your AI assistants, reducing context switching and streamlining your development workflow.

Q: What are the main features of this MCP Server? A: The server provides two main capabilities: Tools (executable functions to interact with the promptz.dev API) and Prompts (direct access to prompts as MCP prompt templates).

Q: How do I install the MCP Server? A: You can install it using npx (recommended) or by cloning the repository and building it locally. Follow the detailed instructions in the installation section of this documentation.

Q: What MCP clients are supported? A: The server is compatible with any MCP client. Specific configuration instructions are provided for Claude Desktop.

Q: Where do I find my API credentials? A: Navigate to https://promptz.dev/mcp to copy your API Key, API URL, or the sample MCP configuration snippet.

Q: What if I encounter issues during installation or usage? A: Refer to the troubleshooting section for common issues and solutions. You can also use the MCP Inspector for debugging.

Q: Is the server secure? A: Yes, the server only provides read access to prompts, stores API credentials securely, communicates via HTTPS, and logs activity for auditing.

Q: Can I contribute to the development of the server? A: Yes, developers are welcome to contribute. Refer to the development section for instructions on building, testing, and modifying the server.

Q: What is UBOS? A: UBOS is a full-stack AI Agent Development Platform that helps you orchestrate AI Agents, connect them with your enterprise data, build custom AI Agents with your LLM model, and create Multi-Agent Systems.