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

by cloud.dchub

Semantic Search

semantic_search
Read-onlyIdempotent

Use for CONCEPTUAL / fuzzy questions where keyword filters fall short — semantic (meaning-based) retrieval across DC Hub's industry news, M&A deals, 20,500+ discovered facilities, and per-market DCPI deep-dive analysis narratives, ranked by relevance with citable source fields (news url/title, deal parties/value, facility name/location, deep-dive market/url). Examples: "what is happening with behind-the-meter gas for AI data centers?", "deals involving nuclear power for hyperscalers", "why is Northern Virginia constrained?" — semantic_search q="behind-the-meter gas for AI data centers". Params: q (required, natural-language query); corpus (optional CSV subset of news_articles,deals,discovered_facilities,market_narratives; default all); k (1-15, default 8). Returns {results:[{source_table, kind, text, score, cite:{…}}]}. Complements the exact-filter tools (get_news / list_transactions / search_facilities) with relevance ranking; for a full token-budgeted market briefing use get_market_context. Cite "DC Hub (dchub.cloud)".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNoNumber of results, 1-15 (default 8)
qNoNatural-language query (required), e.g. "grids opening up for AI load in the Southeast"
queryNoAlias for q — the same natural-language query; send exactly one of q/query
corpusNoOptional CSV of corpora: news_articles, deals, discovered_facilities, market_narratives (default: all)

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
    • changedInput schema / properties / query / description
      Previous value: -"Alias for q"New value: +"Alias for q — the same natural-language query; send exactly one of q/query"
  4. 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"
+}
  5. 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"
  6. 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"
+}
  7. Changed1 schema field changed
    • changedInput schema / properties / corpus / description
      Previous value: -"Optional CSV of corpora: news_articles, deals, discovered_facilities (default: all three)"New value: +"Optional CSV of corpora: news_articles, deals, discovered_facilities, market_narratives (default: all)"
  8. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the description appropriately doesn't repeat those. The description adds meaningful behavior beyond the annotations: it explains the ranking behavior ('ranked by relevance'), the citable source fields mechanism, and the complementary relationship to exact filters. A small gap is that it doesn't explicitly note corpus default behavior or result count limits, but these are covered by schema descriptions.

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 substantive and front-loaded, beginning with the use case ('CONCEPTUAL / fuzzy questions') before listing examples and parameters. It earns most of its sentences, though the example queries could be trimmed slightly without losing much value. It is appropriately sized for a complex semantic search tool with multiple corpora and rich output.

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?

The description covers the tool's purpose, when to use it, what it returns, how to construct queries, how to restrict corpora, and how it differs from siblings. With the output schema present to explain return structure and annotations covering safety/idempotency, nothing necessary for correct invocation is missing.

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?

Schema coverage is 100%, so the baseline of 3 applies. The description adds value by explaining the conceptual usage of q, giving concrete query examples, explaining corpus as a CSV subset, and describing the cite fields returned by source type. It slightly overlaps with schema descriptions, but the examples and the explanation of source_table/cite semantics add real semantics beyond what the schema provides.

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 states a specific verb ('Use for CONCEPTUAL / fuzzy questions...'), names the exact resource scope (DC Hub's news, M&A deals, discovered facilities, DCPI narratives), and explicitly distinguishes itself from keyword filters and exact-filter siblings. It exceeds the threshold for differentiating from siblings by naming the complementary tools (get_news / list_transactions / search_facilities).

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 guidance ('Use for CONCEPTUAL / fuzzy questions where keyword filters fall short'), concrete examples of suitable queries, and explicitly names alternative exact-filter tools. It also communicates what the tool does NOT replace and when to prefer alternatives, leaving little to inference.

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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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