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Long-running tasks are an open topic of discussion, and I think MCP intends to address it in the future.

There are a few proposals floating around, but one issue is that you don't always know whether a task will be long-running, so having separate APIs for long-running tasks vs "regular" tool calls doesn't fully address the problem.

I've written a proposal to solve the problem in a more holistic way: https://github.com/modelcontextprotocol/modelcontextprotocol...



It'd be nice to more closely integrate MCP into something like Airflow, with hints as to expected completion time.

Real world LLM is going to be built on non-negligible (and increasingly complicated) deterministic tools, so might as well integrate with the 'for all possible workflows' use case.


I'm not familiar with Airflow, but MCP supports progress notifications: https://modelcontextprotocol.io/specification/2025-03-26/bas...


DAG workflow scheduling. https://github.com/apache/airflow




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