Frequently Asked Questions (FAQ) about AI Sticky Notes - MCP Server

Q: What is MCP? A: MCP stands for Message Control Protocol. It is an open protocol that standardizes how applications provide context to Large Language Models (LLMs), allowing AI models to access and interact with external data sources and tools.

Q: What is the AI Sticky Notes - MCP Server? A: It’s a Python project demonstrating a minimal MCP server using the mcp SDK. It lets you create and manage sticky notes that can be read, updated, and summarized by an AI agent like Claude, via Claude Desktop.

Q: What are the key features of this server? A: The server allows you to add and save notes, read all saved notes, fetch the latest note, and prompt Claude to summarize all notes.

Q: What are the requirements to run this server? A: You need Python 3.8+, Claude Desktop installed, uv (recommended), and the MCP Python SDK.

Q: How do I install the dependencies? A: It is recommended to install uv by running the following code based on your operating system, Windows: irm https://astral.sh/uv/install.ps1 | iex and macOS/Linux: curl -LsSf https://astral.sh/uv/install.sh | sh. Then use uv init . and uv add mcp-cli to install the required dependencies.

Q: How do I integrate this with Claude Desktop? A: Open Claude Desktop, go to Settings > Developer > Edit Config, add your MCP server using the generated uv command, and restart Claude.

Q: How do I use this server with Claude? A: Ask Claude things like “Add a note saying ‘Meeting at 3 PM’”, “Read all my notes”, “What’s the latest note?”, or “Summarize my notes”.

Q: What are some potential future enhancements? A: Some ideas include multi-user note support, adding timestamps to notes, searching notes by keyword, and AI-generated tags or categories.

Q: Where can I find more AI tools and solutions? A: Check out the UBOS Asset Marketplace for more AI-powered tools and solutions.

Q: How does UBOS support AI Agent Development? 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 Multi-Agent Systems.