A simple application demonstrating Model Context Protocol (MCP) integration with FastAPI and Streamlit, allowing users to interact with LLMs through a clean interface.
An MCP server that allows AI assistants to utilize human capabilities by sending requests to humans and receiving their responses through a Streamlit UI.
A Streamlit-based web application that generates personalized learning paths by integrating with YouTube, Google Drive, and Notion services through the Model Context Protocol.
A server that routes user questions to specialized agents (date, location, weather) or an LLM expert, with a simple Streamlit web interface for easy interaction.
Enables comprehensive PDF analysis and manipulation including page size analysis, chapter extraction, splitting, compression, merging, and conversion to images. Provides both MCP server interface for AI assistants and Streamlit web interface for direct user interaction.