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

Find Sites

find_sites
Read-onlyIdempotent

FRONT DOOR CHECK — if the question spans more than one capability ("find 200MW near Dallas with fiber, then rank the markets"), call execute_plan(intent="<the user's question, unchanged>"). find_sites is the right single call when the user has NO site yet and wants candidates to start from — the first step of data center site selection. THE INVERSE QUERY: every other DC Hub siting tool needs a coordinate you already have — analyze_site scores one, get_composite_site_score grades one, rank_sites orders candidates YOU already enriched, find_alternatives needs a seed facility. This one answers "where should I even be looking?". Returns candidate SEARCH AREAS anchored on real HIFLD substations at or above min_voltage_kv, spatially de-duplicated by cluster_km so a dense metro yields distinct areas instead of 40 near-identical rows, each carrying measured distance to the nearest gas pipeline and fiber route plus state-grain moratorium context, and a next_calls handoff. ★ WHAT A CANDIDATE IS NOT: a search area is NOT a parcel, NOT a listing, and NOT land known to be for sale — DC Hub holds no land-ownership or availability data, and hosted parcel boundaries cover ONE county (Loudoun VA), so analyze_parcel will 404 on most of these points BY DESIGN. Read each as "start looking here", then score the coordinate with analyze_site. ★ READ constraint_coverage BEFORE CALLING THIS A SCREENED LIST: a constraint filters ONLY when its layer actually answered. If a layer errors, the set comes back UNFILTERED with applied:false plus a reason and an instead, the names repeated in top-level unapplied_constraints and an unapplied_constraints_warning — an unevaluable constraint is never a passed constraint. fiber_distance_km is a straight-line CHORD between a route's endpoints, NOT the true polyline path; its basis is stamped on every candidate and get_fiber_readiness at the coordinate is the engineered read. hazard/moratorium are STATE grain, never a site verdict. A geography is REQUIRED — pass state, or lat+lon (+radius_km); without one you get a legible 400 (error_code geography_required), never a nationwide scan. Free tier coarsens coordinates to ~11 km and withholds operator/capacity. Answers "where should I even be looking for 200 MW in Ohio" and "which areas near Dallas sit on 230kV with gas within 5 miles". Try: find_sites state=OH min_voltage_kv=230 max_gas_km=8 — or find_sites lat=39.04 lon=-77.48 radius_km=60 min_voltage_kv=500. Do NOT use to score a site you already have (analyze_site), to rank candidates you already enriched (rank_sites), to find similar FACILITIES to a known one (find_alternatives), or for interconnection-queue survivors (get_refined_queue).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude of a search centre, e.g. 39.04 — use with lon (+ radius_km) instead of state
lngNoAlias for lon — either name works
lonNoLongitude of a search centre, e.g. -77.48
limitNoMax results to return (1-500; default varies by tool)
stateNo2-letter US state to search, e.g. OH — required unless you pass lat + lon
latitudeNoAlias for lat — either name works
longitudeNoAlias for lon — either name works
radius_kmNoSearch radius in km around lat/lon (default 80, clamped 5-400); ignored in state mode
cluster_kmNoCollapse anchors within this many km into one candidate area (default 8, max 100). Raise it for broader coverage, lower it for denser results
max_gas_kmNoDrop candidates farther than this from the nearest gas pipeline. Applied ONLY if the gas layer answers — check constraint_coverage
max_fiber_kmNoDrop candidates farther than this from the nearest fiber route (CHORD approximation — see fiber_distance_basis). Applied ONLY if the fiber layer answers
min_voltage_kvNoOnly anchor on substations at or above this voltage in kV (default 115). 230+ for hyperscale, 500 for the largest campuses
exclude_moratoriumNotrue = drop candidates in a state with a published data-center moratorium. STATE grain, not jurisdiction grain

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.

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark readOnlyHint=true and idempotentHint=true, so the description correctly reflects a non-destructive search. It adds substantial behavioral context: candidates are search areas, not parcels or listings (and why), constraint_coverage semantics (unfiltered with applied:false on layer errors), fiber_distance as chord not polyline, state-grain hazard/moratorium, geography requirement yielding a 400 error, and free-tier coordinate coarsening. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long (several paragraphs) but well-structured with clear sections (FRONT DOOR CHECK, WHAT A CANDIDATE IS NOT, READ constraint_coverage BEFORE...). It front-loads the most critical routing decision (execute_plan vs find_sites) and then adds necessary caveats. Every sentence adds value, though it could be tightened; the repeated 'where should I even be looking?' appears three times. Still, it earns a 4 for effective structure.

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 (13 params, many siblings, output schema exists), the description is remarkably complete. It covers usage, exclusions, parameter semantics, error handling (geography_required), free-tier limitations, and provides examples. It also mentions the next_calls handoff and that output schema exists, so the agent knows the return structure is defined. Nothing essential is missing for a correct call.

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?

Though the schema covers 100% of parameters, the description enriches meaning: min_voltage_kv default and thresholds (230+ for hyperscale, 500 for largest), cluster_km collapse behavior, max_gas_km applied only if layer answers, max_fiber_km chord approximation, exclude_moratorium state grain, radius_km default and clamp, and alias equivalences (lng/latitude/longitude). It also provides two concrete call examples that demonstrate parameter combinations.

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-resource pair ('find sites' = discover candidate search areas) and immediately differentiates it from siblings: it is 'the first step of data center site selection' answering 'where should I even be looking?'. It explicitly contrasts with analyze_site, rank_sites, and find_alternatives, so an agent can distinguish it without opening schemas.

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 gives explicit when-to-use and when-not-to-use guidance. It says to call execute_plan for multi-capability questions, then enumerates the inverse query and lists 'Do NOT use to score a site you already have (analyze_site), to rank candidates you already enriched (rank_sites), to find similar FACILITIES to a known one (find_alternatives), or for interconnection-queue survivors (get_refined_queue)'. This is exhaustive and unambiguous.

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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