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DC Hub — Data Center & Power Intelligence

by cloud.dchub

Get Changes

get_changes
Read-onlyIdempotent

Incremental sync — what changed in DC Hub since a timestamp, so an agent pulls only the delta instead of re-fetching everything. Returns DCPI 7-day market movers, newly discovered facilities, new M&A deals + news — PLUS, for keyed callers with saved sites, a portfolio block answering "did MY sites move?": per-saved-site verdict flips (CAUTION → BUILD), excess-power deltas, alerts fired, and new facilities near each site since your last check. Pass since= or shorthand "24h"/"7d" (default 24h); cache the response generated_at and pass it back next call. Answers "what changed since I last looked", "anything new this week I should know about". Try: get_changes since=7d.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (1-500; default varies by tool)
sinceNoReturn changes since this ISO-8601 timestamp (YYYY-MM-DD or full datetime) or shorthand "24h"/"7d"; default 24h

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

A4.7/5.0
Behavior5/5

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

The description goes well beyond the annotations by detailing the conditional portfolio block for keyed callers, the per-site verdict flips, excess-power deltas, alerts fired, and new facilities near each site. It also discloses the important sync behavior of caching generated_at and passing it back, which is non-obvious and valuable for correct invocation.

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 dense but every sentence earns its place: purpose, return contents, conditional behavior, parameter guidance, example query, and answer-form matching. It is front-loaded with the core concept and avoids filler while covering a complex tool efficiently.

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 tool of moderate complexity with an output schema, the description is remarkably complete. It covers the sync mechanism, the exact categories of returned changes, the conditional portfolio block for saved-site callers, the generated_at caching pattern, and the practical 'what changed' use cases. No critical operational detail appears 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 is 3. The description adds meaningful usage detail beyond the schema by showing actual invocation patterns ('since=7d'), explaining the default of 24h, and tying the since parameter to the cached generated_at field. This elevates it to a 4.

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 opens with a specific, action-oriented definition: 'Incremental sync — what changed in DC Hub since a timestamp', clearly identifying the resource (DC Hub changes) and the operation (pulling only the delta). This distinguishes it from sibling data-lookup tools like get_news or get_facility by focusing on what changed over time rather than current state.

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

Usage Guidelines4/5

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

The description explicitly frames when to use it: 'so an agent pulls only the delta instead of re-fetching everything' and gives natural-language triggers like 'what changed since I last looked'. It does not name specific alternative tools or exclusions, but the context strongly implies the intended use case, meriting a 4 rather than a 5.

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