XRPL-Utilities
XR-Telemetry

XR-Telemetry

Live XRPL macro telemetry

Supply, regional flows, AMM depth, and a modeled Active Float showing how much XRP can clear inside a single ledger close, all from on-chain data. No price predictions. No investment advice. No black-box math.

Live snapshot

Run a real snapshot

Free from this page. No wallet, no payment, no inputs. The same payload agents pay for over the x402 API at telemetry.xrpl-utilities.io.

Active Float

3-second settlement supply

Total Circulating Supply is how much XRP exists outside Ripple's escrow. Modeled Active Float is how much of that can actually clear inside a single 3-5 second ledger close. Most XRP held at exchanges is sitting in customer balances, not posted on the order book, so the active slice is much smaller than the headline number.

Total Circulating Supply
-
Total XRPL supply minus Ripple escrow.
Modeled Active Float (M)
-
10% of exchange-held XRP, plus XRP committed to liquidity pools, plus XRP resting in open offers on XRPL's native order book.
How to read this

When an exchange holds ~6.5B XRP across its labeled wallets, most of that is user balances backing trades and withdrawals, not depth a market sweep can hit inside a few seconds. Counting full exchange holdings as "available" overstates how much can clear in a settlement burst.

Active Float applies an 10% multiplier on exchange holdings as an estimate of what's genuinely on the book at any moment, then adds XRP committed to liquidity pools (swappable inside a single ledger close) and XRP resting in open offers on XRPL's native order book. The paid /scan response includes every input number and the multiplier so anyone receiving the data can recompute under their own assumptions.

Burst Math

Required equilibrium price calculator

The Equation of Exchange (M · V = P · Q) says supply available for trade times turnover rate equals the per-unit price times annual dollar volume. Plug in three values, solve for the fourth.

M is anchored at Modeled Active Float (the supply that can clear inside a single ledger close). Set Q (your assumption about annual settlement volume on XRPL) and V (how often that supply turns over per year), and the math returns P: the per-XRP price the identity requires under those specific assumptions. Not a forecast. Read P as "what the math requires."

Active depth proxy ratio
Industry range 5–15% · default 10%
10.0%

What fraction of custodial exchange holdings is genuinely posted on the book at any given moment, available to be hit by a market sweep within a few seconds. The midpoint (10%) is the default; drag the slider to see how M (and the equilibrium price P below) responds across the defensible range.

M · Active Float (XRP)
exchange omnibus × 10% + AMM-locked + DEX depth
Formula
P = Q ÷ (V × M)
Solve for USD per XRP
P · Required equilibrium price
-
USD per XRP · algorithmic utility floor
Current spot
-
Market premium over equilibrium floor: -
M = 10% of exchange-held XRP + XRP in liquidity pools + XRP resting in open offers on XRPL's native order book.
Reading the variables

M · Modeled Active Float. The supply that can clear inside a single 3-5 second ledger close. Computed as 10% of exchange holdings + XRP committed to liquidity pools + XRP resting in open offers on XRPL's native order book.

V · Annual velocity. How many times each unit of M is reused for settlement per year. Your assumption. The default of 6 reflects what a mature settlement network looks like with ODL-style cross-border flows recycling supply. Today's real velocity is much lower since most XRP is held, not transacted.

Q · Total annual settlement volume in USD. Your assumption. Must share V's time window (both are annual).

P · The per-XRP USD price the identity requires given M, V, and Q. Not a forecast.

What it means

P usually comes out far below market price. That's the point: pure settlement math is a floor, not a forecast. The gap is everything else XRP is priced for (adoption bets, scarcity, store-of-value), and none of that is in this calculation by design.

What would push P up

  • Q rises · more real annual settlement on XRPL. Plausible drivers: new ODL corridors, treasury B2B adoption, agent-payable x402 flows scaling, RLUSD volume growth.
  • M shrinks · less XRP resting on open markets. Plausible drivers: institutions move into cold custody, AMM pools grow, market makers pull back resting depth.

The Floor Matrix below compounds either dynamic forward 24 months.

Q sanity-check from ETF flow

The /scan response also carries an algebraic_p_at_assumed_qv_usd_flows_biased field next to the canonical P. It applies a bounded nudge (±10% max) to Q based on how tightly ETF AUM moves with XRPL exchange flow over the trailing window: tighter alignment nudges Q up, decoupling nudges down. The canonical P stays operator-controlled so the headline doesn't move with weekly noise; the biased value is a side-by-side comparator only.

Measured settlement volume

What XRPL actually settled

XRP or RLUSD Payments on validated mainnet ledgers, USD-anchored at each ledger's close-time price. Other IOU tokens are excluded. Per-token oracle pricing would distort the figure.

Last 24 hours
-
 
Last 7 days
-
 
Last 30 days
-
 
Annualized run-rate
-
 
 
Permissioned vs open-market
Share of last-24h settlement routed through XLS-81 permissioned venues
Permissioned (XLS-81)
 
Open-market
 
Historical volume
USD per bucket · daily 30 / weekly 12 / monthly 12
Reading this against your Q

The Q field above (in Burst Math) is your assumption about annual XRPL settlement that uses XRP as the medium. The annualized run-rate here is what the network actually transacted this week, projected to a year. If your Q is far above measured Q, you're betting on growth; if it's below, your model is conservative relative to current activity. Click Use measured next to Q to load the live number into the floor calculation.

Why XRP-only feeds Q. RLUSD↔RLUSD payments on XRPL clear through the issuer's stablecoin and don't consume XRP supply, so including them would inflate the demand on Active Float and overstate the equilibrium-price floor. Use measured prefills Q with the XRP-denominated portion of the annualized run-rate. The full XRP+RLUSD figure is shown above for context but isn't what feeds the floor math.

Measured DEX pair volume

What the XRPL order book traded

XRP↔RLUSD order-book fills on validated mainnet ledgers. A taker offer crossing one maker offer counts as one fill; multi-leg crosses contribute one fill per consumed maker leg. AMM swaps and pathfinder-routed legs are not in this number yet.

Last 24 hours
-
 
Annualized run-rate
-
 
Different denominator than settlement

The settlement-volume number above counts gross Payment deliveries: a $100 RLUSD payment that routes through an XRP↔RLUSD offer contributes $100 to that headline. This DEX pair-volume number counts order-book fills: the same Payment also consumed one maker-side offer, and that fill is what shows up here. Both figures can describe the same on-chain transaction in different lenses.

Each fill is recorded with both legs (XRP value at hourly close-time price + RLUSD at $1), so the headline matches the conventional "pair volume" figure that XRPL explorers publish. The XRP-side and RLUSD-side subtotals are shown in the small print for flow-direction views.

Predictive Floor Matrix

24-month projection

Burst Math gives you a price today. Real networks compound: supply tightens, settlement grows. Pick monthly rates below and the math projects forward 24 months. Shaded band is a ±15% visual envelope, not a confidence interval. Grey dashed line is today's market price.

X axis: months from now. Baseline = starting price × ((1 + growth) ÷ (1 − constriction))i. Shaded band = ±15%. Grey dashed line = today's market price.
0%1.5%

% of liquid M that exits circulation each month (vault locks, escrow relock, dormancy growth, AMM TVL). Range capped at 1.5%/month; sustained constriction above that is not historically observed on XRPL.

0%2%

% monthly increase in annual settlement Q (new ODL corridors, B2B adoption, RLUSD scale). Range capped at 2%/month; sustained growth above that compounds into headline-grabbing numbers that the underlying math cannot honestly defend.

Starting price (today)
-
Tweak Q or V above to re-anchor.
Projected price at month 24
-

Small monthly rates compound aggressively. 1% per month of supply constriction works out to ~21% of supply gone in 24 months; 2% monthly volume growth compounds to ~1.6× Q. Watch where the baseline crosses the dashed market line. Sensitivity, not forecast.

How to read the controls

Starting price · today's implied floor. Copied live from Burst Math. Re-anchor by tweaking Q or V there.

Monthly supply constriction · how fast liquid M shrinks each month. 1% per month means 1% of M exits each month into AMM pools, cold custody, escrow, or dormancy.

Monthly volume growth · how fast annual settlement Q grows each month. Compounds geometrically.

±15% band · visual reminder that the baseline is a point estimate. Not a statistical confidence interval. The slider ranges (constriction max 1.5%, growth max 2%) are intentionally narrow: wider ranges produce numbers the model cannot honestly defend.

For developers & AI agents

Pay $0.10 per snapshot, no API key

XR-Telemetry implements x402 v2 with the exact scheme on XRPL mainnet. Verification and settlement are delegated to the t54 XRPL facilitator.

  1. 1. POST /quote returns an invoice with amount in drops, recipient, deep link, and QR code.
  2. 2. Pay the XRPL Payment from any wallet. Poll GET /status/{invoice_id} until paid: true.
  3. 3. GET /results/{invoice_id} returns the full TelemetryPayload: supply, liquidity, AMM, utility floor.
Free MCP tools (3)
  • xrpl_telemetry_settlement_totals
  • xrpl_telemetry_settlement_series
  • xrpl_telemetry_dex_pair_volume
Paid MCP tools (4)
  • xrpl_telemetry_snapshot · $0.10 (inline x402)
  • xrpl_telemetry_get_quote · $0.10 (invoice flow step 1)
  • xrpl_telemetry_get_status · no extra (step 2)
  • xrpl_telemetry_get_results · no extra (step 3)

Or skip the integration: call any tool above from an MCP client (Claude Desktop etc.) via @xrpl-utilities/mcp or the hosted endpoint at mcp.xrpl-utilities.io/mcp. Free tools work without a payment header; paid tools use the same x402 model wrapped as MCP arguments.

# pip install x402-xrpl requests
import requests

quote = requests.post(
    "https://telemetry.xrpl-utilities.io/quote",
    json={},
).json()

# Sign & submit XRPL Payment from your wallet using quote["deep_link"]
# Then poll until paid:
while not requests.get(
    f"https://telemetry.xrpl-utilities.io/status/{quote['invoice_id']}"
).json()["paid"]:
    time.sleep(5)

payload = requests.get(
    f"https://telemetry.xrpl-utilities.io/results/{quote['invoice_id']}"
).json()

print(payload["supply"])
print(payload["utility_floor"])

Output shape

What you get back

Full field-level details at /schema. Live manifest at /agents.json.

Sister products

Also part of the XRPL-Utilities Portfolio

Safe harbor & compliance

XR-Telemetry produces on-chain telemetry and an algebraic implied-floor computation. Not a price prediction, investment recommendation, or financial advice. Burst Math and Floor Matrix are sensitivity tools. They show what the math implies under explicit assumptions, not what XRP will or should be priced at.

Users are responsible for complying with local digital asset and AI regulations, including the California Digital Financial Assets Law and the Colorado AI Act where applicable.

Operational SLA

30-day uptime, measured

Live aggregate from /sla?days=30. The recorder probes our upstream dependencies on a recurring cadence and counts each sample as healthy only if all succeed. Same liveness assertion /healthz returns. No external monitoring; data is what we see from inside the service.

30-day uptime
-
 
24-hour uptime
-
 
Target
-
5-min sample interval
What this number covers

Covered: backend liveness of the XRPL RPC dependency and the x402 facilitator. If either probe fails at sample time, that sample counts as unhealthy and is attributed to its component.

Not covered: external network latency between you and the service, individual endpoint correctness (only liveness), and data freshness inside the snapshot cache. For data freshness, see /healthz checks.slow_tasks.