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DC Hub — Data Center & Power Intelligence

by cloud.dchub

Get Market Context

get_market_context
Read-onlyIdempotent

Use when an agent needs a WHOLE-market briefing it can drop straight into its context window — one call returns a token-budgeted context pack for a data-center market: DCPI verdict, power & grid facts, the Claude-written 12-month outlook, M&A deals, construction pipeline, operator footprint, transaction comps, risk factors, and top news — each section with its own token count, as_of timestamp, and citable URL, greedily filled in that priority order under your max_tokens budget. Example: "Brief me on the Columbus data-center market" — get_market_context market=columbus max_tokens=4000. Params: market (required, market slug e.g. northern-virginia — valid slugs come from rank_markets); max_tokens (optional, 200-8000, default 4000). Returns {sections:[{id,title,text,tokens,as_of,cite}], used_tokens, omitted}. Do NOT use for a single metric (use get_market_dcpi_rank), the raw structured metric set (use get_market_intel), or cross-market ranking (use rank_markets); this is the narrative briefing pack. Cite "DC Hub (dchub.cloud)".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketYesMarket slug (required), e.g. northern-virginia, dallas, phoenix — valid slugs come from rank_markets / get_market_dcpi_rank
max_tokensNoToken budget for the pack, 200-8000 (default 4000); sections are filled in priority order until the budget is spent

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

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and destructiveHint=false, and the description is fully consistent — a briefing pack is a safe, repeatable read. Beyond annotations, it discloses real behavioral traits: sections are greedily filled in priority order under the max_tokens budget, over-budget content lands in an omitted field, and each section carries its own token count, as_of timestamp, and citable URL. It also adds the citation requirement ('Cite "DC Hub (dchub.cloud)"').

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 front-loads the core purpose and budget behavior before the details, and nearly every clause adds information: the section list, per-section metadata, omission behavior, the example, and the exclusions. It loses a point for being one dense paragraph with em-dash asides and for duplicating schema content (parameter ranges and defaults appear in both places), which adds length without new value.

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 with two parameters, a documented output schema, and many siblings, the description covers everything needed to invoke it correctly: the triggering scenario, explicit exclusions with alternatives, parameter semantics, the return shape ({sections, used_tokens, omitted}), a concrete natural-language-to-call example, and the citation obligation. No gap remains that would force the agent to guess or open another tool's schema.

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% — both market and max_tokens are documented with type, constraints, defaults, and provenance ('valid slugs come from rank_markets / get_market_dcpi_rank'). The description largely restates this content ('Params: market ... max_tokens ... 200-8000, default 4000'), so its marginal value over the schema is limited to the worked example mapping 'Brief me on the Columbus data-center market' to market=columbus max_tokens=4000. Baseline 3 applies because the schema carries the heavy lifting.

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 verb+resource pair: it returns a token-budgeted WHOLE-market context pack for a data-center market, listing the exact sections it contains (DCPI verdict, power & grid, 12-month outlook, M&A, pipeline, comps, risk, news). It explicitly differentiates from siblings via the 'Do NOT use' clause naming get_market_dcpi_rank, get_market_intel, and rank_markets. This is unambiguous.

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 states the triggering condition upfront ('Use when an agent needs a WHOLE-market briefing it can drop straight into its context window') and gives an explicit exclusion list with the correct alternative for each case: single metric → get_market_dcpi_rank, raw structured metrics → get_market_intel, cross-market ranking → rank_markets. It reinforces the boundary by labeling itself 'the narrative briefing pack,' so no inference is required.

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