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Manage Massed Compute GPU instances, VMs, and billing audits through AI.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Massed Compute MCP Server" yet — see the docs or source repo.
List the currently available Massed Compute GPU instance types, regions, pricing, and stock status, then rank them by cost-performance.
A list of available GPU resources with pricing, regions, and ranked recommendations.
Create a GPU VM suitable for LLM fine-tuning, choose an appropriate configuration, and return the instance details and connection method after launch.
A provisioned and running VM with its configuration, status, and access instructions.
Review my GPU instance usage and billing records for the last 30 days, identify unusual charges, idle instances, and cost-saving opportunities.
A billing audit summary highlighting anomalous costs, idle resources, and optimization suggestions.
Manage AutoDL GPU instances, SSH access, file transfers, and GPU monitoring.
Manage Azure infrastructure and cloud resources using natural language commands.
Query normalized usage, cost, and dashboard data across OpenAI and Anthropic.
Manage Linode cloud resources via API for instance lifecycle operations.
Parse multi-cloud IaC and generate real-time cost estimates and comparisons.
Manage OpenStack cloud resources and infrastructure operations through AI assistance.