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Monitor and manage Modal training jobs for long-running GPU workloads.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mdl-train-mcp" yet — see the docs or source repo.
Please check the current training job status on Modal and tell me whether it is still running, the latest progress, and whether there are any abnormal signals.
A summary of the job's running status, latest progress, and any issues that need attention.
Help me inspect this long-running GPU training job and summarize the key status information without dumping large amounts of raw logs.
A concise training status overview that makes it easy to judge whether the job is progressing normally.
As an automation assistant, periodically check the Modal training job and report the current status in concise summaries, avoiding excessive log output.
Status summaries suitable for automation workflows, highlighting key information instead of full logs.
Developers or researchers running long training jobs on Modal can use it to quickly inspect current status and progress without manually reading large logs.
When an LLM agent needs to keep an eye on training jobs, this MCP tool can provide status information that is easier to read and summarize programmatically.
It is an MCP server for monitoring and managing training jobs on Modal. It is specifically aimed at LLMs or automation assistants that need to check long-running GPU training without being overwhelmed by log output.
It is suitable for long-running GPU training jobs, especially when status and progress need to be checked regularly. The provided information does not specify more task types.
The provided material does not include installation steps, runtime requirements, or key configuration details. For prerequisites, see the source repository.
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Let MCP-aware agents use Modal serverless compute, GPUs, and headless browsing.