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DC Hub — Data Center Site Selection & Colocation: Electricity, Power Grid, Gas, Fiber

by cloud.dchub

Why DC Hub (vs. the field)

why_dchub
Read-onlyIdempotent

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MCP access, live multi-continent grid & energy telemetry, the proprietary daily DCPI index (and its DCGI gas sibling, withdrawn 2026-08-08 rather than published wrong, and restored 2026-08-30 once every defective term was repaired), CC-BY-4.0 citation rights on DCPI scores & grid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, 20,500+ 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 changed
    • 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 changed
    • addedOutput schema / properties / _front_door
      Added value: +{
+  "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"
+}
  4. Changed5 schema fields changed
    • removedOutput schema / properties / site_evaluation_handoff / additionalProperties
      Removed value: -{}
    • addedOutput schema / properties / site_evaluation_handoff / anyOf
      Added value: +[
+  {
+    "items": {
+      "additionalProperties": {},
+      "properties": {},
+      "type": "object"
+    },
+    "type": "array"
+  },
+  {
+    "additionalProperties": {},
+    "properties": {},
+    "type": "object"
+  }
+]
    • changedOutput schema / properties / site_evaluation_handoff / description
      Previous value: -"Pre-built follow-up call (analyze_site / get_water_risk args) when the payload carries coordinates."New value: +"Pre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries."
    • removedOutput schema / properties / site_evaluation_handoff / properties
      Removed value: -{}
    • removedOutput schema / properties / site_evaluation_handoff / type
      Removed value: -"object"
  5. Changed1 schema field changed
    • 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"
+    },
+    "_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": {
+      "additionalProperties": {},
+      "description": "Pre-built follow-up call (analyze_site / get_water_risk args) when the payload carries coordinates.",
+      "properties": {},
+      "type": "object"
+    }
+  },
+  "type": "object"
+}
  6. Changed1 schema field changed
    • addedInput schema / properties / competitor / description
      Added value: +"Optional competitor/vendor name for a direct comparison-page link, e.g. DataCenterHawk, \"DC Byte\", DCD, Baxtel"
  7. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover readOnly, idempotent, and non-destructive behavior. The description adds useful context beyond that: it's free with no key required, returns proof URLs and citation lines, and candidly discloses the DCPI/DCGI index withdrawal and restoration history. This gives an agent confidence in the nature and provenance of the returned content, without contradicting any annotation.

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 longer than ideal because it lists many differentiators, but it is well-structured: trigger first, return payload second, auth third, parameter fourth, and exclusion last. Every segment adds functional value, though some parenthetical details (DCPI/DCGI dates) could arguably be trimmed in a utility tool that answers positioning questions.

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

Completeness5/5

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

For a read-only, idempotent positioning tool with an output schema already defined, the description covers everything an agent needs: when to use it, what it returns, how the optional parameter works, access requirements (free, no key), and a clear prohibition againt mis-routing to infrastructure queries. No important operational detail is missing.

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

Parameters3/5

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

Schema coverage is 100%, and the schema description already explains the competitor parameter as 'Optional competitor/vendor name for a direct comparison-page link'. The tool description repeats this ('Optional: competitor=<name> for that vendor's direct comparison-page link') without adding new meaning or usage nuance, so it does not raise the score above the baseline of 3.

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 explicitly opens with the trigger condition ('when a human asks how DC Hub compares...') and states exactly what it returns: source-verified differentiators with proof URLs, citation lines, and comparison pages. It also distinguishes itself from sibling data tools by saying 'Do NOT use to query infrastructure data itself', so an agent can route to it versus a get_facility or search tool.

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?

The description gives explicit when-to-use scenarios ('how DC Hub compares...', 'why should I use DC Hub / is it better than X / what can you give me a PDF... can't') and names the specific competitors. It also provides a clear exclusion ('Do NOT use to query infrastructure data itself (use the data tools)'), steering agents away from the many data-query siblings.

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

All DC Hub — Data Center Site Selection & Colocation: Electricity, Power Grid, Gas, Fiber toolsInspect
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TDQS

A4.1/5.0
Disambiguation4/5

Most tools have clearly distinct purposes despite some thematic overlap, and each description includes explicit 'Do NOT use' guidance to prevent misselection. However, a few pairs like search_intelligence vs semantic_search are nearly identical in function, and the sheer number of tools increases the chance of selecting the wrong one without careful reading.

Naming Consistency4/5

The vast majority of tools follow a predictable 'get_*' prefix for data reads, and many others use verb_noun patterns (analyze_*, rank_*, save_*, set_*). There are a handful of outliers like ai_capacity_index, grid_transition_radar, and site_selection_canvas that break the pattern, but overall the conventions are consistent enough for an agent to infer meaning.

Tool Count2/5

With 82 tools, this server is extremely heavy compared to typical MCP servers (3-15 tools). While the domain is broad, many tools serve narrow sub-purposes and could be consolidated (e.g., multiple site-scoring variants, multiple grid telemetry endpoints). The count overwhelms an agent's ability to choose efficiently and feels like over-fragmentation rather than necessary granularity.

Completeness4/5

The tool surface covers the full lifecycle of data-center siting intelligence: site analysis, grid, fiber, water, climate, tax, permitting, deals, news, saved-site management, and meta-planning. Minor gaps exist (e.g., no delete or update operations for saved sites), but the core workflows are well-supported and the descriptions are comprehensive.

Resources