Skip to main content
Glama
azmartone67

DC Hub — Data Center & Energy Intelligence

Get Climate Intel

get_climate_intel
Read-onlyIdempotent

Retrieve USGS seismic hazard and NOAA climate normals for any lat/lon to inform data center structural bracing and cooling design.

Instructions

Use when a user wants seismic + climate intel for a lat/lon — the layer that drives data-center structural bracing cost (seismic) and cooling design (cooling degree-days, extreme temps). Grounded STRICTLY in USGS ASCE 7 (seismic) + NOAA climate normals via ACIS; every value traces to a federal source and missing data is declared unavailable, never estimated. Example: get_climate_intel lat=33.45 lon=-112.07. Returns {seismic_hazard_usgs:{status, peak_ground_acceleration_g, ss, s1, seismic_design_category, hazard_class}, climate_normals_noaa:{status, reference_station:{id,name,distance_km}, cooling_design_metrics:{cooling_degree_days_annual, extreme_max_dry_bulb_f, extreme_max_wet_bulb_f (null if source lacks it), data_vintage}}, overall_climate_summary, data_availability, sources}. radius_km (optional, default 25) snaps to the nearest NOAA station; beyond it climate returns unavailable_exceeds_radius. Seismic is US (ASCE 7); non-US → seismic unavailable. For natural-hazard ratings use get_disaster_risk; for one blended verdict use get_composite_site_score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoSite latitude in decimal degrees (-90 to 90, required), e.g. 33.45
lngNoAlias for lon — either name works
lonNoSite longitude in decimal degrees (-180 to 180, required), e.g. -112.07
latitudeNoAlias for lat — either name works
longitudeNoAlias for lon — either name works
radius_kmNoMax distance (km) to snap to the nearest NOAA station (optional, default 25)

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.
Behavior5/5

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

Annotations already declare read-only/idempotent/non-destructive, and the description adds rich behavioral context: data sources (USGS ASCE 7, NOAA via ACIS), strict grounding policy, missing data declared unavailable never estimated, radius behavior, and return status fields. No contradiction with 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?

Although lengthy, every sentence earns its place: use case, example, return structure, edge cases, and alternatives. Front-loaded with the primary use, then organized details. No filler or repetition.

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 this complexity—two domains, multiple metrics, source constraints, radius logic, and output schema—the description is exceptionally complete. It covers inputs, behavior, limitations, return structure, and alternatives, leaving no critical gaps.

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 descriptions already cover all six parameters with 100% coverage, so baseline is 3. The description adds practical context: explains aliases implicitly via example, clarifies radius_km default and its effect on station snapping, and shows how parameters map to the returned data.

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 explicitly states the tool provides 'seismic + climate intel for a lat/lon' and lists specific metrics (peak ground acceleration, cooling degree-days, etc.). It clearly distinguishes from siblings by naming get_disaster_risk and get_composite_site_score as alternatives for different intents.

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?

Opens with 'Use when a user wants seismic + climate intel for a lat/lon' and provides a concrete example. States exclusions: non-US seismic is unavailable, radius_km snapping behavior, and explicitly points to alternatives for related but different needs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/azmartone67/dchub-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server