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

by cloud.dchub

Industry News

get_news
Read-onlyIdempotent

FRONT DOOR CHECK — if news is only ONE input to a bigger question (is this market heating up, should we still build here), call execute_plan(intent="<the user's question, unchanged>") and let it pull news alongside the market and grid reads. If the user actually wants the headlines, get_news IS the right call — one round trip; do not send a plain news request through the planner. Curated data center industry news from 40+ trade sources (DCD, Data Center Knowledge, Data Center Frontier, Capacity Media, The Register Data Centre, Fierce Telecom, etc.) refreshed every 30 min. Returns title, summary, source, published_at, and the market/operator entities mentioned. Filter by category (deals/permits/outages/policy/AI). Answers "what is happening in the data center industry this week", "any news on AI capacity". Try: get_news category=AI limit=10. The parameter is category, not topic. Industry news only; do NOT use for structured M&A deal data (use list_transactions) or the construction pipeline (use get_pipeline).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (1-500; default varies by tool)
queryNoFree-text keyword to filter news, e.g. "Stargate" or "interconnection queue"
sourceNoRestrict to one trade source, e.g. DCD, "Data Center Frontier", "Capacity Media"
date_toNoLatest published date, ISO-8601 (YYYY-MM-DD)
categoryNoNews topic filter, e.g. deals, permits, outages, policy, AI
date_fromNoEarliest published date, ISO-8601 (YYYY-MM-DD)
min_relevanceNoMinimum relevance score 0-1 to include an item, e.g. 0.5

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. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description does not need to restate safety traits. It adds useful behavior beyond the annotations: refresh cadence, curation scope, one-round-trip behavior, and returned fields. No contradiction exists.

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 front-loaded with the most important routing caveat, and nearly every sentence adds actionable information. It is somewhat long and dense, but the length is justified by the need to disambiguate from several sibling tools.

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 tool has an output schema and strong annotations, and the description still adds the missing contextual pieces: when to use vs. avoid, an example invocation, source scope, refresh frequency, and sibling exclusions. Nothing critical is missing for an agent to select and invoke it correctly.

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?

The schema already documents all 7 parameters with full coverage, so the baseline is 3. The description adds extra value by giving a concrete example call, clarifying that the parameter is 'category' not 'topic', and listing example category values.

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 clearly states that get_news retrieves curated data center industry news from 40+ trade sources and returns fields such as title, summary, source, and published_at. It also distinguishes itself from execute_plan, list_transactions, and get_pipeline by naming exactly what it is not for.

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 'FRONT DOOR CHECK' explicitly tells an agent when to call execute_plan instead of get_news, and when get_news is the right call. It also gives negative boundaries for structured M&A data and pipeline data, naming the correct sibling tools.

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

A3.8/5.0
Disambiguation1/5

With 85 tools, several families are heavily overlapping: semantic_search and search_intelligence are explicitly documented as the same retrieval with different call shapes, save_site and save_to_shortlist both persist sites, and list_saved_sites and get_shortlist both read saved sites. Additionally, site scoring is split across analyze_site, get_composite_site_score, score_facility, and rank_sites, making correct tool selection very difficult for an agent.

Naming Consistency3/5

All names are snake_case and mostly readable, but conventions are mixed: many use get_* (get_facility, get_grid_intelligence), others use verb phrases (analyze_site, compare_isos, rank_markets), and some are bare noun phrases (ai_capacity_index, hyperscaler_deals, grid_transition_radar, site_selection_canvas). The search family alone uses search, search_facilities, semantic_search, and search_intelligence with no consistent pattern.

Tool Count1/5

85 tools is an extreme count for any MCP server, far beyond the 3-15 well-scoped range and above the 50+ threshold described as an extreme mismatch. Even with a wide domain like data-center siting, this many tools overwhelms agent context and makes selection costly.

Completeness4/5

The domain surface is exceptionally broad: siting, grid, gas, fiber, water, climate, tax, permitting, deals, news, facilities, saved shortlists, alerts, webhooks, key management, and research dossiers are all covered with connected workflows. Minor gaps exist, such as no delete or update for saved sites and no pause/resume for standing intents, but these are workable rather than blocking.

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