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au.com.nempulse/nempulse

au.com.nempulse/nempulse · v1.1.1

Australian NEM battery (BESS) data for AI agents: revenue, dispatch, FCAS, events. Free, no auth.

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Reported outcomes

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Last check

Reachable, 11 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

A 96/100

What it does: 11 tools · 11 read, 0 write · Weather

Test call list_bess_units: worked (1,354 ms)

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +6
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +10
  • Read/write annotations: +5
  • Safe test call: +20
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://nempulse.com.au/mcp

Tools

11 tools listed at last check
  • list_bess_units Reference list of every NEM-registered grid-scale battery. Call this first to turn a station name into the DUID the other tools need. Returns the whole fleet in one response (no filters): DUID, station, region, MW/MWh, MLF, coordinates, is_commissioning, commercial_context, unit_class, peer_comparab
  • get_fleet_summary Fleet-wide snapshot for the NEM battery fleet: unit_count, active_unit_count, total_mw, total_mwh, fleet_rev_mtd, avg_efficiency_pct, last_interval and spot_prices (latest price per region, $/MWh). Covers month-to-date unless date_from and date_to are given. fleet_rev_mtd is gross spot revenue (ener
  • get_battery_detail Deep-dive metrics for one battery by DUID (e.g. HPR1 = Hornsdale): revenue, dispatch, SOC, FCAS. WARNING: rev_today, energy_rev_today, fcas_rev_today and contingency_fcas_rev_today are MONTH-TO-DATE by default, not daily (matching the rev_mtd keys in fcas_breakdown) — do not report them as 'today's
  • query_nem_data Last resort for ad hoc questions the other tools cannot answer. Takes a plain-English question, generates SQL over NEMPulse's tables, and returns the SQL, the result rows and a short explanation. It is the slowest tool (can take close to a minute) and it is AI-generated, so check the returned SQL be
  • get_battery_revenue Daily gross-spot revenue by market (energy + FCAS) for one battery (DUID) over a date range. Daily grain only. This is the tool for total revenue questions — use get_battery_optimal only for the actual-vs-perfect-foresight benchmark, not as a revenue source (its 'actual' figure is MLF-adjusted and s
  • get_battery_optimal Actual vs LP-optimal dispatch revenue, per-DUID summary, over a date range (energy-only, perfect-foresight benchmark). NOT a revenue-total source — use get_battery_revenue for that. Both the 'actual' AND the 'optimal' figures here are MLF-adjusted (get_battery_revenue's is gross) — the LP's objectiv
  • list_events List NEM spot-price events, newest first. An event is a run of 5-minute intervals in one region where the price stays above $500/MWh or below -$200/MWh (short gaps are bridged), typed by its peak price: negative (below -$200), elevated (peak $500 to $1,000), spike ($1,000 to $5,000) or extreme ($5,0
  • get_event_detail One price event by event_id (take the id from list_events), with the response of every battery that was online, ranked by est_revenue. Event fields are as in list_events. Each battery row has duid, station, region, response (DISCH = discharging, CHRG = charging, IDLE, OFFLINE = no availability), avg
  • get_regional_prices Daily minimum, maximum and mean regional reference price (RRP, $/MWh) for one NEM region over a date range. Daily summary only: the raw 5-minute price series is not exposed (it is published by AEMO on NEMWEB). Use it for price context around revenue or events. For individual price spikes use list_ev
  • get_simulator_revenue Modelled revenue for a hypothetical 1 MW battery of a given duration in one region (not a real unit), from NEMPulse's optimal-dispatch model on real prices. Returns P10/P50/P90 revenue for three tiers: realistic (forecast-informed result scaled by the capture ratio real batteries achieve, the only t
  • get_rankings League table of merchant NEM batteries over a date range, ranked by capture rate by default (actual revenue as a share of the forecast-informed benchmark; capture_perfect_pct is the share of the perfect-foresight ceiling). Each row has rank, duid, station, region, capacity, duration_band, capture_fc

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