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Magg is a Python library designed to aggregate Machine Control Protocol (MCP) data. It streamlines the collection and management of data, offering functionalities that support various MCPs. Through an easy-to-use API, users can effortlessly manipulate MCP data.

MCP Playground is a Streamlit-based interface that allows users to interact with large language models while seamlessly integrating external Multi-Server Command Protocol (MCP) tools. It enables the deployment of multiple FastMCP servers managed via Docker Compose, creating a provider-agnostic client using LangChain and LangGraph.

The Todo.txt MCP Server is a powerful Model Context Protocol server that connects your todo.txt files to AI assistants. It allows you to manage your todo list using natural language while maintaining the simplicity and portability of the todo.txt format. You can create, update, and delete tasks with AI assistance, and it provides statistics and insights about your productivity. It also integrates seamlessly with existing todo.sh setups.