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    A communication framework that enables multiple AI agents to collaborate through asynchronous messaging, agent registration, and discovery. It facilitates complex task coordination and real-time discussion across distributed agent workflows using the Model Context Protocol.
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    An MCP server that turns AI assistants into competent Festo/CODESYS PLC engineers by grounding them in curated, manufacturer-accurate knowledge and forcing every artifact through a machine-checked validation pipeline for CODESYS import.
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    MIT
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    A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.
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    A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.
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    MIT
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    tdmcp is an open-source (MIT) Model Context Protocol server for TouchDesigner. You describe a visual in plain language and your AI assistant builds the real node network inside TouchDesigner, checks it for errors, and shows a preview — it ships an embedded operator knowledge base so the model uses real operators instead of guessing. TypeScript codebase, runs locally.
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    MIT