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DC Hub — Data Center & Power Intelligence

by cloud.dchub

Citation Block

summarize_for_citation
Read-onlyIdempotent

Use right before you QUOTE a DC Hub figure to a human — it returns one paste-ready attribution line for the value you are about to cite, with the CORRECT licence for that layer. Pass what you read off the response you are citing: subject (what the figure is), as_of (the provenance as_of), url (the row's profile_url or dcpi_url), completeness (the completeness flag), and layer. ★ LICENCE IS PER LAYER AND THIS IS THE POINT: DCPI scores, verdicts, band thresholds, methodology and DC Hub's own grid/site analysis are CC-BY-4.0 and yours to quote with attribution; the facility inventory and third-party physical layers are COMPOSITES whose upstream terms DC Hub cannot waive (parts are OpenStreetMap, ODbL 1.0, share-alike), so they carry a pointer to https://dchub.cloud/data-sources instead of a grant. A flat "CC-BY-4.0" over a facility record is an over-claim. Returns {citation_text, cite_as, license, license_basis, source, url, as_of, as_of_basis, completeness, omitted}. Free, no key, no network call — it assembles what you pass and never resolves or invents a value. If you omit as_of the line says RETRIEVED rather than claiming a data date, and tells you which field to pass next time. Do NOT use to look a figure UP (call the data tool first); this cites a figure you already have.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoThe profile_url or dcpi_url from the cited row. Must be a dchub.cloud URL; anything else is dropped and named in `omitted`.
as_ofNoThe as_of you read off the cited response (provenance.as_of). Omit it and the line says RETRIEVED instead of claiming a data date.
layerNoWhich layer the figure came from: dcpi | grid_analysis | facility_inventory | physical_infrastructure | deals | other. Decides the licence line; omit and you get the scoped statement rather than a grant.
subjectNoWhat you are citing, in the words you will show the human, e.g. "Ashburn DCPI verdict" or "ERCOT interconnection queue depth"
completenessNoThe completeness flag from the cited response, if it carried one

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.

TDQS

A5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, and the description adds substantial behavioral context beyond those: it is 'Free, no key, no network call', it 'never resolves or invents a value', it handles omitted as_of by saying RETRIEVED, and it explains per-layer licensing logic with an over-claim warning. No contradiction with annotations exists.

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

Conciseness5/5

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

The description is long but every sentence earns its place. It starts with the when and what, then enumerates inputs, then explains the critical per-layer licensing nuance that prevents over-claims, then notes output fields and the no-network behavior. The negative instruction is explicit. It is front-loaded and structured for impact.

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?

Given the tool's licensing complexity and the need to avoid mis-claiming CC-BY-4.0, the description is complete: it covers all five parameters, describes the output object, states network/key requirements, explains the RETRIEVED fallback, and distinguishes itself from lookup tools. An output schema exists, so the description need not enumerate return fields, yet it still mentions the key ones.

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

Parameters5/5

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

Schema coverage is 100%, but the description goes further by explaining the role of each parameter in context: subject is 'what you are citing', as_of is 'the provenance as_of', url is 'the row's profile_url or dcpi_url', and layer 'decides the licence line'. It also explains consequences of omitting as_of and layer, adding real semantic value beyond the schema.

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 and resource: 'returns one paste-ready attribution line' for a DC Hub figure the agent is about to quote. It clearly distinguishes itself from the data-retrieval sibling tools by saying 'Do NOT use to look a figure UP (call the data tool first); this cites a figure you already have.'

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 explicitly says when to use it ('Use right before you QUOTE a DC Hub figure to a human') and when not to use it ('Do NOT use to look a figure UP'). It also names the alternative behavior: 'call the data tool first'. This leaves no ambiguity about the tool's role among many siblings.

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