What is an MCP Server?

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

What file formats does the MCP Development Framework support?

The framework supports PDF, Word, and Excel files. It automatically detects the file type and uses the appropriate processing tool.

How can I deploy the MCP Server?

You can deploy the server using Docker (recommended) or through a traditional Python deployment. Docker deployment is simpler and more streamlined.

How do I develop a new tool for the MCP Development Framework?

Create a new Python file in the tools directory, inherit from the BaseTool class, register your tool with the @ToolRegistry.register decorator, and implement the execute method.

What are the key features of the PDF processing tool?

The PDF tool supports quick preview and full analysis modes, extracts text and images, and handles large files efficiently. It also uses a multi-layered processing strategy to ensure accuracy and stability.

Can the MCP Server retrieve content from any website?

Yes, the URL tool can retrieve content from any webpage, handling HTTP errors and encoding issues automatically.

What is UBOS and how does it relate to the MCP Server?

UBOS is a full-stack AI Agent Development Platform that complements the MCP Server by providing a comprehensive environment for developing and deploying AI agents. It allows you to orchestrate AI Agents, connect them with your enterprise data, build custom AI Agents with your LLM model, and create Multi-Agent Systems.