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Glama

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

Analyze Site

analyze_site
Read-onlyIdempotent

Use when a user has ONE specific lat/lon (a parcel, a candidate site) and wants the full multi-factor data-center suitability read in one call. Example: "Score this Phoenix parcel for a 100MW build — power, gas, fiber, market & risk." — analyze_site lat=33.45 lon=-112.07 capacity_mw=100 state=AZ. Params: lat (-90 to 90, required unless candidate_id or location), lon (-180 to 180, required unless candidate_id or location), location (a market NAME or metro slug instead of coordinates, e.g. location="ashburn" — resolved to that market's PUBLISHED CENTROID through the DCPI market row, with a resolved_from block naming what it resolved to; a MARKET-level read, NOT the parcel you named, and a trailing state is not stripped so "Ashburn, VA" will not resolve), candidate_id (a cand_… from get_refined_queue — resolves coordinates from the frozen mint and ignores lat/lon), capacity_mw (target load in MW, e.g. 50-500 — returns a capacity_context block sizing that load against nearby installed generation; it deliberately does NOT move overall_score, and the block names where the load IS applied), state (2-letter US, optional — improves the tax-incentive/context lookup), include_grid/include_risk/include_fiber (booleans, default true). Returns (full, paid): {overall_score (aka composite_score, 0-100 composite — for the integrity-first version that never imputes a missing factor, use get_composite_site_score), interpretation (verdict string, e.g. "Excellent site"), scores{power_infrastructure, gas_pipeline_access, fiber_connectivity, market_conditions, risk_resilience — each 0-100}, nearby{substations_50km, power_plants_80km, gas_pipelines_50km, facilities_100km, fiber_carriers_in_state, generation_capacity_mw, total_capacity_mw}, power_cost{industrial_cents_kwh, commercial_cents_kwh, period, basis}, fiber{connectivity_score, nearest_carrier_km, near_net_bucket, top_carriers[], single_carrier_risk}, location, citation}. FREE tier returns a REAL, citable HEADLINE — composite_score + verdict + the single top limiting factor (the lowest sub-score) + citation; the full per-factor breakdown, nearby infrastructure, power cost, fiber carriers, and the branded Site Analysis PDF (generate_site_analysis) are Pro. For dedicated water / disaster / climate / tax reads use get_water_risk / get_disaster_risk / get_climate_intel / get_tax_incentives. Do NOT use to compare 2+ sites (use compare_sites) or to find sites that match a target (use find_alternatives).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoSite latitude in decimal degrees (-90 to 90; required unless candidate_id or location given), e.g. 33.45
lngNoAlias for lon — either name works
lonNoSite longitude in decimal degrees (-180 to 180; required unless candidate_id or location given), e.g. -112.07
stateNoUS state abbreviation (optional) — improves the tax-incentive lookup, e.g. AZ
mpp_payNoAutonomous payment (Stripe MPP), step 1: set true to receive a signed $0.50 payment challenge for this call instead of the free preview. No money moves — a challenge is a price quote. Humans never set this, so it does not affect the normal free/trial funnel.
latitudeNoAlias for lat — either name works
locationNoMarket NAME or metro slug instead of coordinates, e.g. "ashburn", "northern-virginia", "dallas". Resolved to that market's PUBLISHED CENTROID through the DCPI market row, and the answer carries a resolved_from block saying so. This is a MARKET-level read, not the parcel you named — pass lat/lon for a specific site. Not an alias for lat/lon: a place name is not a coordinate.
longitudeNoAlias for lon — either name works
capacity_mwNoTarget power load for the build in megawatts (MW), e.g. 100 (typical 50-500)
candidate_idNoPREFERRED for queue survivors: a cand_… id from get_refined_queue — coordinates come from the FROZEN mint (lat/lon args are ignored; zero transcription drift; expired ids fail closed with candidate_expired). See dchub.cloud/docs/candidate-lifecycle
include_gridNoInclude grid-headroom / substation analysis (default true)
include_riskNoInclude water/drought/climate risk analysis (default true)
include_fiberNoInclude fiber-connectivity analysis (default true)
mpp_credentialNoAutonomous payment (Stripe MPP), step 2: the Shared Payment Token you minted for challenges[0]. Set it here to pay $0.50 for this single call and receive the full result — no API key, no subscription, no human. One payment covers one call.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
fiberNoFiber read: {connectivity_score, nearest_carrier_km, near_net_bucket, top_carriers[], single_carrier_risk} (full payload)
quotaNoCaller quota state (remaining calls, tier) when available.
lockedNoWhich sections are Pro-locked on the free headline: {per_factor_breakdown, nearby_infrastructure, power_cost, fiber_carriers, site_analysis_report}
nearbyNoNearby infrastructure counts: {substations_50km, power_plants_80km, gas_pipelines_50km, facilities_100km, fiber_carriers_in_state, generation_capacity_mw, total_capacity_mw} (full payload)
scoresNoPer-factor breakdown (full/paid payload)
_entityNoPayload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.
previewNoHeadline preview line (free tier)
verdictNoVerdict string, e.g. "Excellent site" / BUILD-CAUTION-AVOID read
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.
locationNoEcho of the analyzed location (full payload)
power_costNoPower cost read: {industrial_cents_kwh, commercial_cents_kwh, period, basis} (full payload)
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.
overall_scoreNoAlias of composite_score on the full payload
site_headlineNotrue when this is the free citable HEADLINE (score + verdict + limiting factor)
interpretationNoVerdict prose on the full payload
composite_scoreNo0-100 composite site suitability score (free HEADLINE tier and full tier)
limiting_factorNoSingle top limiting factor (the lowest sub-score) — always present on the free headline
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

A5/5.0
Behavior5/5

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

Beyond annotations, the description discloses major behavioral nuances: location resolves to a market's PUBLISHED CENTROID and is 'a MARKET-level read, NOT the parcel you named'; 'Ashburn, VA' will not resolve because trailing state is not stripped; capacity_mw deliberately does NOT move overall_score; candidate_id uses the frozen mint and ignores lat/lon; free vs Pro tier output differences are explicit. These are exactly the non-obvious traits an agent needs, and none contradict the annotations.

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—usage, example, parameter semantics, return breakdown, free/Pro division, and sibling alternatives are all packed in. It is front-loaded with the primary use case and example, and the dense structure mirrors the tool's complexity. No filler or tautology.

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 complexity (14 params, optionality logic, tiered output, resolution edge cases), the description is remarkably complete. It covers invocation, parameter behavior, return structure, free/paid differences, and exclusions, so an agent can call it correctly without external lookup. The output schema exists, and the description still explains the headline output and what the full paid result includes.

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 adds meaning beyond the schema: it explains the optionality condition among lat/lon, location, and candidate_id; clarifies that location is a market-level lookup with centroid resolution; notes capacity_mw returns a capacity_context and intentionally leaves overall_score unchanged; and states the defaults for include_* booleans. This goes well beyond the schema's basic type/description.

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: a full multi-factor data-center suitability read for ONE specific lat/lon parcel or candidate site. It distinguishes itself from siblings by explicitly naming compare_sites, find_alternatives, get_water_risk, get_disaster_risk, get_climate_intel, get_tax_incentives, and get_composite_site_score as alternatives for other intents. This gives an agent a clear, non-confusable purpose.

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 opens with 'Use when a user has ONE specific lat/lon...' and provides a concrete example invocation. It explicitly states when NOT to use the tool ('Do NOT use to compare 2+ sites' / 'to find sites that match a target') with named alternatives. It also routes dedicated water/disaster/climate/tax reads to their specialized tools, leaving no ambiguity about selection.

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

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.