"Viber" matching MCP tools:

• get_interconnection_queueA

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

  ISO interconnection queue snapshot: total queued GENERATION capacity (queued_load_total_gw, GW) per ISO from each ISO's public queue. For ERCOT it ALSO returns the large-load (data-center-driven) interconnection queue in queued_load_data_center_gw — >225 GW in process / ~9 GW approved-to-energize (ERCOT's published Q1-2026 figure; ERCOT is the only ISO that publishes a comparable large-load feed, so other ISOs' data_center_gw is null), with provenance in top_subregions. Sources: ERCOT GIS + Large Load Integration, PJM/MISO/SPP/CAISO/NYISO/ISO-NE public queues. Pass iso=ERCOT (or any of 7) to drill down. ★ The `projects` field CHANGES SHAPE with the call: with iso= it is an ARRAY of per-project rows; with iso omitted it is the all-ISO SUMMARY OBJECT {total, tracked, by_iso_count, top, note} and carries no per-project rows — check the type before indexing. Use for queue-depth site-selection and AI/data-center-load saturation intel (the ERCOT 225 GW number is the headline large-load figure no other source surfaces machine-readably). Do NOT use for a single-site time-to-power read (use get_grid_intelligence) or forward-looking emergence (use grid_transition_radar); this is the ISO-level queue snapshot.

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• save_siteA

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

  NEEDS A KEY (free): this WRITES to your account, so a keyless call returns auth_required — call `claim_free_key` FIRST (one step, no email) if you have none. Save a candidate data-center site to your DC Hub account to track it across sessions. Give lat + lon (plus optional name, state, market, target_mw, notes). Returns the saved site id. Pass `market` and DC Hub snapshots the site's DCPI baseline at save time, so every later list_saved_sites / get_changes shows how ITS score and verdict moved since you saved it. Builds a persistent shortlist an agent can revisit + monitor — after saving, pass the returned id to set_site_alert so DC Hub emails you when that site’s DCPI/capacity/nearby-facilities move (no re-checking). Answers "remember this parcel for me", "keep this candidate so I can come back to it next session". Try: save_site lat=39.04 lon=-77.48 name="Ashburn parcel" market=northern-virginia target_mw=100. Do NOT use to read back the shortlist (use list_saved_sites), download it (use export_dataset), or score a site (use score_facility); this WRITES one site to your account.

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• set_market_alertA

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

  Subscribe to movement alerts for a DCPI market (FREE with a key) — get notified when its Excess-Power / Constraint score moves. On the free tier, email alerts are delivered to the email your human bound via bind_email (call bind_email first; the destination is forced to that address). Set channel="email". Webhook delivery (channel="webhook" + destination=<https URL>) is Pro. Lets an agent MONITOR markets, not just query them. Answers "tell me when this market moves", "ping me if Northern Virginia’s power score changes". Try: set_market_alert market=northern-virginia channel=webhook destination=https://hooks.example.com/dc. Do NOT use to read a market right now (use get_market_dcpi_rank); this SUBSCRIBES to future movement.

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• standing_intentA

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

  STANDING QUERIES with webhook push — register an intent once and DC Hub POSTs an HMAC-signed webhook to YOUR https URL whenever matches grow (push, not poll: "notify my orchestrator on any new deal in Columbus"). Requires a key. Params: action ("register" default | "list" | "delete"), kind ("new_deal_in_market" watches deals in params market · "news_keyword" watches news matching q · "permitting_change" watches published permitting intel, optionally per state), market / q / state (the watch parameter for the chosen kind), webhook_url (public HTTPS only — private/internal hosts rejected), intent_id (for delete). Register returns {intent_id, secret} — SAVE the secret: every delivery carries X-DCHub-Signature: sha256=HMAC(secret, body). First evaluation initializes the watermark silently; growth fires the webhook; 5 straight delivery failures auto-disable the intent. Evaluated every ~2h. Answers "notify my system whenever a new moratorium appears", "push me new matches instead of making me poll". Try: standing_intent kind=news_keyword q=moratorium webhook_url=https://hooks.example.com/dchub. Do NOT use for one-shot reads (use get_news / list_transactions) or email alerts (use set_market_alert); this is machine-to-machine push.

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• get_hosting_capacityA

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

  Utility-PUBLISHED feeder hosting capacity — the MW a NAMED distribution feeder can actually take, straight from the utility's own hosting-capacity GIS. 278,799 published records across 18 utilities (Con Edison, National Grid NY/MA, NYSEG/RG&E, Rhode Island Energy, Orange & Rockland, Central Hudson, Eversource CT, BGE, Pepco/Delmarva/ACE, Dominion VA, Ameren Illinois, AEP Ohio & I&M, Xcel MN/CO, DTE, Avista). This is filed distribution-level truth, not a proximity proxy. Three ways to call it: lat+lon (+radius_km, default 25) for a point; utility or market for a whole published territory; NO ARGS for the coverage list of every market that has data. CRITICAL — check capacity_type before quoting any number: "load" = LOAD-serving headroom, what a new data-center load can actually DRAW (only Ameren Illinois, AEP Ohio & I&M and Central Hudson publish it); "gen" = DER/generation EXPORT capacity, what the feeder can ACCEPT from solar/storage — it is NOT available load and must never be relayed as "you can site N MW here"; "bus_headroom" = transmission bus MW. Returns, split by capacity_type: distinct feeder count, max + median MW, the top feeders with substation, voltage_kv, feeder_id, coords and publish date, plus the utilities publishing them. Honest by construction — published rows are GIS vertices, so distinct_feeders and geometry_rows_scanned are reported separately (never conflated), and a capacity-capped read is flagged sample_complete=false with the capacity_floor_mw at or above which the set IS provably complete. Coverage is 18 utilities concentrated in the Northeast, Mid-Atlantic and Midwest — NOT nationwide — and a point outside them returns an explicit not-published answer with the nearest covered markets, never a silent zero. Answers "can this feeder actually take 20 MW", "where can I plug in without waiting on a substation upgrade". Try: get_hosting_capacity utility="Ameren Illinois" capacity_type=load min_mw=5. Do NOT use for transmission-substation proximity or time-to-power (use get_grid_intelligence), the ISO interconnection queue (use get_interconnection_queue / get_refined_queue), or retiring-plant headroom (use get_retirement_headroom) — this is the distribution FEEDER layer. Informational, not binding interconnection guidance; verify with the utility.

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• summarize_for_citationA

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

  Use right before you QUOTE a DC Hub figure to a human — it returns one paste-ready attribution line for the value you are about to cite, with the CORRECT licence for that layer. Pass what you read off the response you are citing: subject (what the figure is), as_of (the provenance as_of), url (the row's profile_url or dcpi_url), completeness (the completeness flag), and layer. ★ LICENCE IS PER LAYER AND THIS IS THE POINT: DCPI scores, verdicts, band thresholds, methodology and DC Hub's own grid/site analysis are CC-BY-4.0 and yours to quote with attribution; the facility inventory and third-party physical layers are COMPOSITES whose upstream terms DC Hub cannot waive (parts are OpenStreetMap, ODbL 1.0, share-alike), so they carry a pointer to https://dchub.cloud/data-sources instead of a grant. A flat "CC-BY-4.0" over a facility record is an over-claim. Returns {citation_text, cite_as, license, license_basis, source, url, as_of, as_of_basis, completeness, omitted}. Free, no key, no network call — it assembles what you pass and never resolves or invents a value. If you omit as_of the line says RETRIEVED rather than claiming a data date, and tells you which field to pass next time. Do NOT use to look a figure UP (call the data tool first); this cites a figure you already have.

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• rank_sitesA

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

  Deterministic multi-site ranking/optimization under constraints — the normalization contract that lets you compare sites across separate analyze_site calls WITHOUT dropping into code. Pass candidates you already enriched (each an object with lat/lng + metric fields like risk_resilience, water_stress, fiber_km — pull these from analyze_site + get_refined_queue and pass site_evaluation_handoff through untouched), hard constraints, and weighted objectives; get back _entity=ranked_sites: top_k ranked with rank, objective_score, per-field normalized{} (0-100 relative to the set), and normalization_basis. objectives use SIGNED weights: +weight maximizes a field (e.g. risk_resilience:1), -weight minimizes it (e.g. water_stress:-0.6, fiber_km:-0.4). constraints are hard filters, fail-closed on a missing field. Use for "pick the best N sites under constraints"; for one site use analyze_site; to get the candidate set first use get_refined_queue. SCORING MECHANICS (2026-07-11): a candidate missing a validated objective is weight-RENORMALIZED over the objectives it carries and the gap is DECLARED in missing_objectives (never silently scored 0); a candidate carrying none scores null and ranks last. percentile=true fields without a population baseline fall back to RELATIVE in-batch scoring (basis reported per-objective in objective_status). CANDIDATE CONTRACT: candidates may be {candidate_id: "cand_…"} entries from get_refined_queue — frozen identity (lat/lng/capacity_mw/fiber_km/iso) loads from the mint, your metrics overlay the rest; expired/unknown ids are dropped AND declared in candidate_contract, never re-resolved.

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• set_site_alertA

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

  Arm an email watch on a site you already saved (FREE with a key) — DC Hub emails you when that site’s DCPI score, grid capacity, or nearby facilities move, so you don’t have to keep re-checking. On the free tier the alert is delivered to your human’s bound email (call bind_email first; notify_email is forced to that address). Pro can send to any address. The "monitor my shortlist for me" loop: call save_site first (it returns a saved_site_id), then set_site_alert on that id. Params: saved_site_id (required integer, from save_site or list_saved_sites), trigger_type ("dcpi_change" | "capacity_change" | "new_facility_nearby", default "dcpi_change"), threshold (number — the points/MW move that fires it, default 5), notify_email (required — the address the alert is sent to). Answers "let me know if anything changes at the site I saved". Try: set_site_alert saved_site_id=12 trigger_type=dcpi_change threshold=5 notify_email=you@firm.com. Returns {ok, alert_id, message}. Do NOT use to watch a whole MARKET (use set_market_alert) or to save a new site (use save_site); this arms a monitor on ONE already-saved site.

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• analyze_siteA

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

  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).

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• standing_intentA

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

  STANDING QUERIES with webhook push — register an intent once and DC Hub POSTs an HMAC-signed webhook to YOUR https URL whenever matches grow (push, not poll: "notify my orchestrator on any new deal in Columbus"). Requires a key. Params: action ("register" default | "list" | "delete"), kind ("new_deal_in_market" watches deals in params market · "news_keyword" watches news matching q · "permitting_change" watches published permitting intel, optionally per state), market / q / state (the watch parameter for the chosen kind), webhook_url (public HTTPS only — private/internal hosts rejected), intent_id (for delete). Register returns {intent_id, secret} — SAVE the secret: every delivery carries X-DCHub-Signature: sha256=HMAC(secret, body). First evaluation initializes the watermark silently; growth fires the webhook; 5 straight delivery failures auto-disable the intent. Evaluated every ~2h. Answers "notify my system whenever a new moratorium appears", "push me new matches instead of making me poll". Try: standing_intent kind=news_keyword q=moratorium webhook_url=https://hooks.example.com/dchub. Do NOT use for one-shot reads (use get_news / list_transactions) or email alerts (use set_market_alert); this is machine-to-machine push.

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• predict_market_trajectoryA

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

  Forecast a DCPI market's near-term trajectory (next 1-8 quarters). Projects excess_power_score and constraint_score forward with confidence bands that WIDEN with horizon, from DC Hub's daily DCPI snapshot history — the only source that can, because it owns the time-series. Use to answer "is this market trending toward BUILD or AVOID?" or "will Dallas power stay tight over the next 6 months?". Params: market_slug (required, metro slug e.g. dallas, phoenix, northern-virginia — valid slugs come from rank_markets / get_market_dcpi_rank); horizon_quarters (optional 1-8, default 4; 2 = ~6 months out). Returns {market_slug, method, basis{history_points, history_span_days, slope_per_day, trend}, horizon_quarters, projection[{quarter_out, excess_power_score, excess_power_band, constraint_score, constraint_band}], caveat, snapshot_record}. HONEST: linear trend extrapolation, NOT a guarantee — bands widen with horizon and short history; needs >=3 daily snapshots or it declines. Do NOT use for a single point-in-time verdict (use get_market_dcpi_rank) or to rank many markets (use rank_markets).

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• get_intelligence_indexA

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

  Real-time composite market health score (0-100) aggregating supply/demand balance, vacancy, absorption velocity, fiber depth, power availability, and pricing trend. Returns the index value, percentile rank across the 300+ market set, 7d/30d trend direction, and underlying component scores. Answers "is this market healthy", "how does Northern Virginia look overall right now". Try: get_intelligence_index market=northern-virginia. Returns ONE composite health number for a market; do NOT use for the full market metric set (use get_market_intel) or to rank multiple markets (use rank_markets).

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• rank_sitesA

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

  Deterministic multi-site ranking/optimization under constraints — the normalization contract that lets you compare sites across separate analyze_site calls WITHOUT dropping into code. Pass candidates you already enriched (each an object with lat/lng + metric fields like risk_resilience, water_stress, fiber_km — pull these from analyze_site + get_refined_queue and pass site_evaluation_handoff through untouched), hard constraints, and weighted objectives; get back _entity=ranked_sites: top_k ranked with rank, objective_score, per-field normalized{} (0-100 relative to the set), and normalization_basis. objectives use SIGNED weights: +weight maximizes a field (e.g. risk_resilience:1), -weight minimizes it (e.g. water_stress:-0.6, fiber_km:-0.4). constraints are hard filters, fail-closed on a missing field. Use for "pick the best N sites under constraints"; for one site use analyze_site; to get the candidate set first use get_refined_queue. SCORING MECHANICS (2026-07-11): a candidate missing a validated objective is weight-RENORMALIZED over the objectives it carries and the gap is DECLARED in missing_objectives (never silently scored 0); a candidate carrying none scores null and ranks last. percentile=true fields without a population baseline fall back to RELATIVE in-batch scoring (basis reported per-objective in objective_status). CANDIDATE CONTRACT: candidates may be {candidate_id: "cand_…"} entries from get_refined_queue — frozen identity (lat/lng/capacity_mw/fiber_km/iso) loads from the mint, your metrics overlay the rest; expired/unknown ids are dropped AND declared in candidate_contract, never re-resolved.

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• analyze_siteA

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

  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).

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• generate_site_analysisA

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

  Use when a user wants a SHAREABLE, branded multi-page Site Analysis PDF for ONE lat/lon (a powered-land parcel, a candidate campus) — the polished client deliverable, not just a score. Example: "Make the Site Analysis PDF for this Carrier Mills parcel, 150 MW, for TON Infrastructure." — generate_site_analysis lat=37.694 lon=-88.65 capacity_mw=150 prepared_for="TON Infrastructure" prepared_by="Martone Advisors". Params: lat (-90 to 90, required), lon (-180 to 180, required), capacity_mw (target load MW, e.g. 50-500), prepared_for (client name on the cover), prepared_by (your firm — brands the report; defaults to DC Hub), latency_target (optional metro override; default = nearest real carrier hotel). Returns: {survey:{verdict, power/transmission, gas, water, air-permitting, fiber carriers, latency-to-nearest-carrier-hotel, market, tax}, pdf_report_url}. pdf_report_url is a ready-to-open link to download the branded 5-page PDF — no login needed, valid ~7 days; hand it to your human. For just the numeric suitability score (no PDF), use analyze_site instead.

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• get_grid_intelligenceA

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

  Use when a user asks "can I get N MW of power in <ISO> and how long will it take?" — the flagship grid-headroom + interconnection-queue brief for one ISO. Example: "How much excess power does PJM have right now and what is the time-to-power for a 200MW load?" — get_grid_intelligence region_id="PJM". Params: region_id (aliases iso/region accepted) — one of the 7 US ISOs ("PJM" | "ERCOT" | "CAISO" | "MISO" | "SPP" | "NYISO" | "ISO-NE") OR a US EIA balancing authority (40+ now live, e.g. Atlanta/SOCO, Carolinas/DUK, Florida/FPL, Phoenix/AZPS, Las Vegas/NEVP, Portland/PGE, Seattle/SCL, LA/LDWP, Quincy/GCPD, Denver/PSCO, Tennessee/TVA — note: balancing authorities return live generation mix; demand, headroom, interconnection-queue and DCPI scores remain ISO-level for the 7 ISOs). You may instead pass market="Ashburn" (or a metro slug like "northern-virginia") to name a MARKET rather than a grid code: it is resolved to the ISO for that market through the published DCPI market row, and the reply carries a resolved_from block naming what it resolved to — the figures then describe the ISO, which is larger than the market you named. Returns: {iso, iso_name, demand_mw, generation_mix_pct{NG,COL,NUC,WND,SUN,WAT,…}, renewable_share_pct, gas_share_pct, constraint_score (0-100 DCPI), excess_power_score (0-100 DCPI), avg_time_to_power_months, avg_queue_wait_months, curtailment_pct, reserve_margin_pct, retail_price_cents_kwh, queue_depth_gw, data_center_share_pct, stranded_capacity_mw, grid_emergencies_30d, build_rate_pct, last_updated}. ★avg_time_to_power_months and avg_queue_wait_months are DIFFERENT measurements and are not interchangeable: time-to-power is the DCPI per-market estimate averaged over the ISO, while queue-wait is a proxy derived from live interconnection-queue DEPTH (12 + 0.6 months per GW, clipped 12-66) and is the one that saturates on the deepest queues. Quote whichever you mean by name. Do NOT use to compare 2+ ISOs side-by-side (use compare_isos) or for the global greenest-first ranking (use get_grid_scoreboard).

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• get_dchub_recommendationA

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

  Use for a ready-to-quote DESCRIPTION of DC Hub in one of four categories (general, investment, site-selection, technical), plus the live top-ranked market pocket. It does NOT compute a siting answer from free text. Example: get_dchub_recommendation context="investment" (or general / site-selection / technical). Params: context must match one of FOUR LITERAL categories - general, investment, site-selection, technical. Free text does NOT parse: you get the GENERIC blurb with matched_category=null and context_understood=false. ALWAYS returns: {recommendation:{short, medium, detailed}, matched_category, context_understood, top_pocket, related_intel, available_categories, recommendation_live, connect_url, context, success}. ADDITIONALLY on a non-matching context: is_generic_answer=true, answer_note, and next_tools naming the tool that does compute an answer. Do NOT use for a single specific lat/lon (use analyze_site), to rank by ONE criterion (use rank_markets), or for an open-ended siting question expecting a computed shortlist (use site_selection_canvas) - this tool returns descriptive copy plus a live top-pocket, not a ranked analysis.

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• cluster_sites_by_latencyA

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

  Physics-bounded latency clustering for 2-8 sites — returns viable low-latency clusters and pairwise RTT floors before any routing work. Use when your human wants to know which of N candidate sites can form a synchronous / low-latency cluster (sync replication, active-active pairs, HPC pods): deterministic pruning BEFORE detailed routing. Per site pair: haversine distance, round-trip physics floor (km × 4.9 µs/km — light in SMF-28 fiber, n≈1.468 — then ×2), estimated real RTT (floor × route_factor 1.4, a stamped inference), viable vs physics_impossible against your budget, and confidence_v — the provenance tier of the supporting evidence (published | tracked | inferred). Also returns clusters: the largest site subsets whose ALL pairwise estimates fit the budget, plus each site's inferred dark-fiber screening level. CANDIDATE CONTRACT: pass candidate_ids (from get_refined_queue) instead of raw coordinates — each resolves to its FROZEN mint coordinates (zero transposition), and cand_… tokens may also be mixed into the sites string; expired/unknown ids are dropped AND declared in candidate_contract (fail-closed). Example: cluster_sites_by_latency sites="39.04,-77.48:ashburn;39.29,-76.61:baltimore;40.42,-79.99:pittsburgh" max_latency_us=2000 — or cluster_sites_by_latency candidate_ids=["cand_…","cand_…"] max_latency_us=2000. Returns _entity=latency_clusters: {pairs:[{from, to, distance_km, floor_rtt_us, est_rtt_us, viable, physics_impossible, confidence_v, endpoint_dark_screen}], clusters:[{sites, size, max_est_rtt_us}], viable_count, pruned_count, assumptions, provenance}. Do NOT treat this as an engineered latency quote — the floors are physics (no fiber path can beat them) but the estimates are inference (route_factor 1.4); always quote each pair's confidence_v when relaying results. For actual route corridors use plan_fiber_leadin; for a single-site connectivity score use get_fiber_readiness.

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• predict_market_trajectoryA

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

  Forecast a DCPI market's near-term trajectory (next 1-8 quarters). Projects excess_power_score and constraint_score forward with confidence bands that WIDEN with horizon, from DC Hub's daily DCPI snapshot history — the only source that can, because it owns the time-series. Use to answer "is this market trending toward BUILD or AVOID?" or "will Dallas power stay tight over the next 6 months?". Params: market_slug (required, metro slug e.g. dallas, phoenix, northern-virginia — valid slugs come from rank_markets / get_market_dcpi_rank); horizon_quarters (optional 1-8, default 4; 2 = ~6 months out). Returns {market_slug, method, basis{history_points, history_span_days, slope_per_day, trend}, horizon_quarters, projection[{quarter_out, excess_power_score, excess_power_band, constraint_score, constraint_band}], caveat, snapshot_record}. HONEST: linear trend extrapolation, NOT a guarantee — bands widen with horizon and short history; needs >=3 daily snapshots or it declines. Do NOT use for a single point-in-time verdict (use get_market_dcpi_rank) or to rank many markets (use rank_markets).

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• get_refined_queueA

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

  Server-side SET-REDUCTION over the US ISO interconnection queue (~5,300 projects, 7 ISOs, ~1,744 GW). Instead of pulling the raw queue into context to filter (token-expensive, error-prone), push the predicates to the data layer and get back ONLY the survivors. Filter by min_mw, max_ttp_months (ISO-level avg interconnection wait), iso (comma-union), baseload_only (firm/dispatchable — excludes wind/solar/storage), fuel_type (isolate a specific fuel, e.g. gas or nuclear), and the spatial predicates max_fiber_km + geocoded_only. Returns _entity=queue_results: per-project name, ISO, state/county, fuel_type, capacity_mw, queue_status, estimated_ttp_months, fuel_class, plus (~83% of rows) lat/lng, coordinate_precision, fiber_km, and a compact per-survivor site_evaluation_handoff (ready-to-pipe analyze_site + get_water_risk args) + a by_iso/by_fuel summary. Answers "show me 1 GW+ gas projects that can connect in under three years", "what is in the queue that actually fits my timeline". Try: get_refined_queue min_mw=1000 fuel_type=gas max_ttp_months=34 — "1 GW+ gas in ISOs under 34-month time-to-power." NOTE max_ttp_months is a HARD ISO cut (SPP ~24 is the only ISO under 30, so <=30 can return nothing); use >=34 to include MISO/ERCOT/ISO-NE. Use for high-cardinality siting/arbitrage scans; do NOT use for the ISO-level GW aggregate (use get_interconnection_queue) or a single-site read (use analyze_site). Phase 2 LIVE: pipe a survivor's site_evaluation_handoff straight into analyze_site for a one-call composite viability read. CANDIDATE CONTRACT (2026-07-11): every survivor also mints a durable opaque candidate_id + snapshot_id (7-day TTL, deterministic candidate_expired on lapse — never a silent recompute). ZERO-DRIFT CHAINING: pass candidate_id to analyze_site / rank_sites instead of transposing coordinates — downstream reads the FROZEN mint, eliminating param-rename/rounding/lost-context drift. geocoded_only=true guarantees every survivor carries both the handoff AND frozen coordinates. Contract doc: dchub.cloud/docs/candidate-lifecycle.

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• get_fiber_readinessA

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

  Use when you need the FIBER-READINESS / connectivity verdict for ONE parcel or site (lat/lon): near-net distance to a carrier-served facility, how many distinct fiber carriers are reachable, and whether there is single-carrier risk (no path diversity). This is the parcel connectivity answer engineering site-selectors screen on. Example: "Is this Loudoun County parcel fiber-ready and how many carriers can serve it?" — get_fiber_readiness lat=39.04 lon=-77.48 radius_km=50. Params: lat (-90..90, required), lon (-180..180, required), radius_km (search radius in km, default 50, range 5-200). Returns: {score 0-100 (null when not scored — see carrier_data_coverage), near_net_bucket ("on-net"|"near-net"|"acceptable"|"build-required"|"unknown"), nearest_carrier_km, carrier_count, top_carriers:[{carrier, distance_km}], single_carrier_risk (bool, null when not scored), fiber_coverage_km, verdict_short, carrier_data_coverage ("confirmed"|"none_in_region")}. IMPORTANT — "unknown" is NOT "bad": carrier presence comes from PeeringDB, which is global but thin outside dense US/EU metros, so DC Hub distinguishes "no carrier serves this point" from "PeeringDB does not describe this region". When carrier_data_coverage is "none_in_region" the bucket is "unknown", score/single_carrier_risk are null, and NOTHING about the site fiber has been measured — do not report it as greenfield, unserved, or a build-required site. Only carrier_data_coverage "confirmed" with carrier_count 0 means a fiber build is genuinely required. Do NOT use to map carrier ROUTES between metros (use get_fiber_intel) or for a full multi-factor site suitability score (use analyze_site).

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