ai_capacity_index
AI Compute Capacity Index — ranks data center markets by where 100MW of AI training capacity can land in the next 30/60/90 days. Returns top markets with facility_count, operator_count, deployable_mw estimate (megawatts), hyperscale_ready flag, rack power density and cooling-type signals where fa...
This record as markdown: /tools/cloud-dchub-mcp-server/ai-capacity-index.md
What ai_capacity_index does on Mcp Server
AI agents call ai_capacity_index 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 top markets to return (default 20) |
horizon | integer | — | Deployment horizon in days: 30, 60, or 90 (default 90) |
Parameters from the server's own tool schema.
Why ai_capacity_index is rated Low
Retrieves and ranks market analysis data without modifying systems, executing code, or financial transactions.
From the tool's definition ranks data center markets, returns top markets, facility_count, deployable_mw estimate, composite score
Attacks that exploit this kind of access
The rule that runs ai_capacity_index 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 ai_capacity_index, this is the rule to start with:
ai_capacity_index 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 ai_capacity_index call is checked against it from then on.
Questions about ai_capacity_index
AI Compute Capacity Index — ranks data center markets by where 100MW of AI training capacity can land in the next 30/60/90 days. Returns top markets with facility_count, operator_count, deployable_mw estimate (megawatts), hyperscale_ready flag, rack power density and cooling-type signals where facility data carries them, and composite score (depth + diversity + power). Refreshed Fridays 14:00 UTC. Use for AI capex planning, GPU cluster siting, hyperscaler deal forecasting. Do NOT use for a general best-markets ranking (use rank_markets) or forward grid-emergence (use grid_transition_radar). It is categorised as a Read tool in the Mcp Server MCP Server, which means it retrieves data without modifying state.
ai_capacity_index accepts 2 parameters: limit, horizon. 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 ai_capacity_index: 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.
ai_capacity_index 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 ai_capacity_index 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 ai_capacity_index. 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.
ai_capacity_index 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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