ai_capacity_index
Use this when the user asks where AI compute capacity could land: 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 den...
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
Tool queries and ranks data center capacity intelligence with no write, delete, or financial operations.
From the tool's definition ranks data center markets, returns top markets, facility data signals, 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
Use this when the user asks where AI compute capacity could land: 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. For grid power availability use DCPI (rank_markets ai_ready). 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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