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DC Hub — Data Center & Energy Intelligence

by azmartone67
OverviewSchemaRelated ServersScoreDiscussions(1)
JavaScript
Remote

Why DC Hub (vs. the field)

why_dchub
Read-onlyIdempotent

Answer comparison questions like 'Why use DC Hub instead of DataCenterHawk, DC Byte, DCD, or Baxtel?' Get source-verified differentiators with proof URLs and citation lines for each competitor.

Instructions

Use when a human asks how DC Hub compares to other data-center data sources — DataCenterHawk (DCHawk), DC Byte, Data Center Dynamics (DCD), Data Center Frontier (DCF), Baxtel, datacenters.com — or asks "why should I use DC Hub / is it better than / what can you give me a PDF or directory can't?". Returns DC Hub's honest, source-verified differentiators (agent-native MCP access, live multi-continent grid & energy telemetry, the proprietary daily DCPI index (and its DCGI gas sibling, withdrawn 2026-08-08 rather than published wrong, and restored 2026-08-30 once every defective term was repaired), CC-BY-4.0 citation rights on DCPI scores & grid analysis, 20,400+ facilities + 330,000+ mapped power/grid/gas/fiber assets) each with a proof URL, a citation line, plus the canonical head-to-head comparison pages. Free, no key required. Optional: competitor= for that vendor's direct comparison-page link. Do NOT use to query infrastructure data itself (use the data tools); this answers positioning / "how do you compare" questions with citable facts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
competitorNoOptional competitor/vendor name for a direct comparison-page link, e.g. DataCenterHawk, "DC Byte", DCD, Baxtel

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNoCaller quota state (remaining calls, tier) when available.
_entityNoPayload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.
citationNoMachine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself.
provenanceNoCollection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.
_front_doorNoIn-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.
_return_loopNoSuggested next-session delta call (get_changes since=24h) so you pull only what changed.
site_evaluation_handoffNoPre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedOutput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. Changed5 schema fields changedv2.3.20
    • removedOutput schema / properties / citation / additionalProperties
      Removed value: -{}
    • addedOutput schema / properties / citation / anyOf
      Added value: +[
+  {
+    "additionalProperties": {},
+    "properties": {},
+    "type": "object"
+  },
+  {
+    "type": "string"
+  }
+]
    • changedOutput schema / properties / citation / description
      Previous value: -"Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload."New value: +"Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself."
    • removedOutput schema / properties / citation / properties
      Removed value: -{}
    • removedOutput schema / properties / citation / type
      Removed value: -"object"
  3. Changed1 schema field changedv2.3.12
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": {},
+  "description": "DC Hub envelope: structuredContent mirrors the JSON payload in content[0].text — tool-specific data fields ride at the top level alongside these envelope keys.",
+  "properties": {
+    "_entity": {
+      "description": "Payload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.",
+      "type": "string"
+    },
+    "_front_door": {
+      "additionalProperties": {},
+      "description": "In-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.",
+      "properties": {},
+      "type": "object"
+    },
+    "_return_loop": {
+      "additionalProperties": {},
+      "description": "Suggested next-session delta call (get_changes since=24h) so you pull only what changed.",
+      "properties": {},
+      "type": "object"
+    },
+    "citation": {
+      "additionalProperties": {},
+      "description": "Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload.",
+      "properties": {},
+      "type": "object"
+    },
+    "provenance": {
+      "additionalProperties": {},
+      "description": "Collection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.",
+      "properties": {},
+      "type": "object"
+    },
+    "quota": {
+      "additionalProperties": {},
+      "description": "Caller quota state (remaining calls, tier) when available.",
+      "properties": {},
+      "type": "object"
+    },
+    "site_evaluation_handoff": {
+      "anyOf": [
+        {
+          "items": {
+            "additionalProperties": {},
+            "properties": {},
+            "type": "object"
+          },
+          "type": "array"
+        },
+        {
+          "additionalProperties": {},
+          "properties": {},
+          "type": "object"
+        }
+      ],
+      "description": "Pre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries."
+    }
+  },
+  "type": "object"
+}
  4. Changed1 schema field changedv2.3.6
    • addedInput schema / properties / competitor / description
      Added value: +"Optional competitor/vendor name for a direct comparison-page link, e.g. DataCenterHawk, \"DC Byte\", DCD, Baxtel"
  5. Addedv2.3.1

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark readOnly/idempotent/non-destructive, so the safety-profile bar is lower. The description adds valuable honesty signals: it promises 'honest' differentiators and even discloses a past data withdrawal/restoration for the DCGI index, which sets expectations about source-verification and quality. It could add note that output is largely static/positioning information, but this is adequately covered by the annotation profile.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but each sentence carries functional weight: the trigger, the list of known competitors, the answer scope, and the exclusion. The embedded list of differentiator examples is dense but directly helps an agent anticipate what the response will contain. Slight verbosity from nested parentheticals, but front-loaded with the core use case.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the return-value burden is partly on structured data. The description explains the tool's role, its optional parameter, its safety profile via annotations, and clearly separates it from sibling data-query tools. The only minor gap is that it does not explicitly say what happens when no competitor is supplied, but the schema and phrasing imply the canonical head-to-head comparison pages are always included.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 100% coverage: the single optional parameter 'competitor' is described as 'Optional competitor/vendor name for a direct comparison-page link.' The description adds context by explaining that the optional parameter drives a direct head-to-head page, while the base behavior works without it. The schema alone would make the parameter understandable, so the extra context is modest but useful.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the exact triggering condition ('Use when a human asks how DC Hub compares to other data-center data sources') and lists the main alternatives by name. It clearly states the tool returns differentiators, proof URLs, citation lines, and head-to-head comparison pages, making it easy to distinguish from data-querying siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-to-use ('Use when a human asks how DC Hub compares'), names the competing sources explicitly, and includes a strong exclusion: 'Do NOT use to query infrastructure data itself (use the data tools).' This is model guidance an agent can act on without inferring.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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