From core
Use when the user asks to start, stop, or check Google Compute Engine GPU instances for physics workflows, including retry-start in constrained zones, instance status checks, and zone mapping management.
npx claudepluginhub jacobtutt/mcp-tools --plugin coreThis skill uses the workspace's default tool permissions.
Operate GCP Compute Engine instances for GPU-backed research workflows.
Verifies tests pass on completed feature branch, presents options to merge locally, create GitHub PR, keep as-is or discard; executes choice and cleans up worktree.
Guides root cause investigation for bugs, test failures, unexpected behavior, performance issues, and build failures before proposing fixes.
Writes implementation plans from specs for multi-step tasks, mapping files and breaking into TDD bite-sized steps before coding.
Share bugs, ideas, or general feedback.
Operate GCP Compute Engine instances for GPU-backed research workflows.
Workflow position: this skill mainly supports component (2) Science by managing compute infrastructure for simulation/training runs.
Use these MCP tools first:
local-gcp-gpu.healthlocal-gcp-gpu.instance_statuslocal-gcp-gpu.start_instancelocal-gcp-gpu.stop_instancelocal-gcp-gpu.set_zonelocal-gcp-gpu.list_zonesTypical sequence:
health to confirm local gcloud readiness.instance_status to see current state.start_instance (or stop_instance) for lifecycle action.instance_status again to confirm final state.Before using lifecycle tools, confirm Google Cloud access for the target project.
Run:
gcloud auth login
gcloud auth application-default login
gcloud config set project <project_id>
Optional default for this MCP server:
export GCP_PROJECT_ID="<project_id>"
If GCP_PROJECT_ID is not set, pass project_id explicitly in tool calls.
Required IAM capability in the target project:
compute.instances.getcompute.instances.listcompute.instances.startcompute.instances.stopQuick verification:
gcloud auth list --filter=status:ACTIVE --format='value(account)'
gcloud compute instances list --project <project_id> --limit 5
Use start_instance with explicit project_id and zone on first call for a VM. If it fails due to transient capacity, re-run with larger max_attempts.
Use stop_instance with discard_local_ssd=true unless you explicitly need to preserve Local SSD data and accept associated implications.
When an instance is stable in one zone, store it with set_zone(instance_name, zone) to reduce repeated zone discovery and avoid ambiguity.
This skill is aligned to the current repository implementation:
servers/gce-ops-mcp/src/gce_ops_mcp/server.pyscripts/run-gce-ops-mcp.shIf this skill is copied into fundamental-physics/marketplace, keep the SKILL content but adjust local file paths and server names to the target repository conventions.