site_selection_canvas
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...
This record as markdown: /tools/cloud-dchub-mcp-server/site-selection-canvas.md
What site_selection_canvas does on Mcp Server
AI agents call site_selection_canvas to retrieve information from Mcp Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
limit | integer | — | Number of shortlist markets to return |
region | string | — | Geography scope, e.g. a US state code like TX or a region like us/apac |
verdict | string | — | Optional DCPI verdict filter: BUILD, CAUTION, or AVOID |
max_months | integer | — | Maximum acceptable time-to-power in months, 1-120, e.g. 24 |
capacity_mw | integer | — | Target power load for the build in megawatts (MW), 1-5000, e.g. 100 |
Parameters from the server's own tool schema.
Why site_selection_canvas is rated Low
The tool queries and synthesizes data from the DC Hub Power Index to produce a ranked shortlist and recommendation. It retrieves, ranks, and presents intelligence about markets without creating, modifying, or deleting any data. The severity is medium because the output (site selection decisions) could influence significant capital allocation, but the tool itself only reads and aggregates data.
From the tool's definition 'Guided end-to-end data-center site selection... get a ranked shortlist of US markets... DCPI verdict, excess-power headroom, time-to-power, ISO' and 'One find->rank->shortlist->verdict call over the DC Hub Power Index'
Attacks that exploit this kind of access
The rule that runs site_selection_canvas safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For site_selection_canvas, this is the rule to start with:
site_selection_canvas is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Server, apply this rule, and every site_selection_canvas call is checked against it from then on.
Questions about site_selection_canvas
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. Do NOT use for a single known parcel (use analyze_site) or an open-ended where-should-I-build question (use get_dchub_recommendation); this runs the full find to rank to shortlist to verdict flow. It is categorised as a Read tool in the Mcp Server MCP Server, which means it retrieves data without modifying state.
site_selection_canvas accepts 5 parameters: limit, region, verdict, max_months, capacity_mw. The full parameter table on this page comes from the server's own tool schema.
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 Read tool with low risk. Read-only tools are generally safe to allow by default.
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.
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