This Python implementation offers a state-based agent orchestration system leveraging the Model Context Protocol (MCP) to streamline LLM interactions. It allows for the creation of resources, tools, and prompts, defining clear agent states like planning, researching, and executing tasks. With this tool, you can customize agent behavior, add new states, define custom tools, and integrate with Claude for Desktop to create sophisticated, context-aware AI workflows.