← computeportal.io
INDIVIDUAL MCP TOOL
cp_sandbox_destroy
Destroy a sandbox and release its GPU resources.
LIVE ENDPOINT
https://mcp.computeportal.io/mcp
Connect to this endpoint to inspect the live schema for cp_sandbox_destroy and invoke it with your own arguments.
Indexed input schema
{}Risk classification
Potential side effects detected · medium confidence · heuristic, not a guarantee.
- A tool name or description contains a deletion term.
Parent server
CONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.computeportal]
url = "https://mcp.computeportal.io/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"computeportal": {
"type": "http",
"url": "https://mcp.computeportal.io/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: computeportal
Remote MCP URL: https://mcp.computeportal.io/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"computeportal": {
"url": "https://mcp.computeportal.io/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"computeportal": {
"type": "http",
"url": "https://mcp.computeportal.io/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "computeportal",
"transport": "streamable-http",
"url": "https://mcp.computeportal.io/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
Related tools
cp_deploy— Deploy a service to Compute Portal from a Docker image or a public GitHub repo.cp_service_list— List all running services on Compute Portal.cp_service_status— Get the current status, replica count, and health of a service.cp_service_logs— Fetch the most recent log lines from a running service.cp_scale— Scale a service's replica count or update its CPU/memory resource limits.cp_destroy— Permanently destroy a service and release its resources.cp_gpu_list— List available GPU nodes with specs, utilization, VRAM usage, and temperature.cp_gpu_reserve— Reserve GPU capacity for a fixed duration.