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Manage AutoDL GPU instances, SSH access, file transfers, and GPU monitoring.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "AutoDL MCP Server" yet — see the docs or source repo.
Use the AutoDL MCP Server to create a GPU instance for deep learning training, list its configuration, startup status, public connection method, and check current GPU usage.
Returns the instance creation result, configuration details, connection info, and a GPU monitoring summary.
Using the AutoDL MCP Server, upload local project files to the target instance, install dependencies over SSH, start the training script, and return execution logs and process status.
Returns file transfer results, remote command execution records, log summaries, and task runtime status.
Check the current AutoDL instance list, identify idle instances with low GPU utilization, suggest which ones to stop, and perform shutdown or release actions.
Returns the instance list, selection criteria, action recommendations, and post-operation instance status.
Remotely manage Linux servers via SSH, commands, Docker, files, and code deployment.
Manage Massed Compute GPU instances, VMs, and billing audits through AI.
Manage Linode cloud resources via API for instance lifecycle operations.
Execute SSH commands on remote servers and resume large file transfers.
Manage VPS servers via SSH with commands, file transfer, Docker, and documentation.
Use one MCP server for filesystem, database, web, and system operations.