Guided end-to-end data-center site selection. Give a capacity target + geography + deadline and get a ranked shortlist of US markets (DCPI verdict, excess-power headroom, time-to-power, ISO) — and, with a paid key, the synthesis decision layer: the #1 pick, the why, a build sequence, and risk fla...
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AI agents invoke site_selection_canvas to trigger processes or run actions in Mcp Server. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
site_selection_canvas can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"site_selection_canvas": {
"limits": [
{
"counter": "site_selection_canvas_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Mcp Server policy for all 33 tools.
These attack patterns abuse exactly the kind of access site_selection_canvas gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Guided end-to-end data-center site selection. Give a capacity target + geography + deadline and get a ranked shortlist of US markets (DCPI verdict, excess-power headroom, time-to-power, ISO) — and, with a paid key, the synthesis decision layer: the #1 pick, the why, a build sequence, and risk flags. One find->rank->shortlist->verdict call over the DC Hub Power Index. Try: site_selection_canvas capacity_mw=100 region=TX max_months=24.. It is categorised as a Execute tool in the Mcp Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mcp Server MCP server in PolicyLayer and add a rule for site_selection_canvas: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp Server. Nothing to install.
site_selection_canvas is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the site_selection_canvas rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for site_selection_canvas. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
site_selection_canvas is provided by the Mcp Server MCP server (https://dchub.cloud/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 33 Mcp Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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