"Ripple" matching MCP tools:

• power_supply_decouplingA

  calc.engineerA

  Select bypass and bulk decoupling capacitors for IC power supply pins. Computes the target PDN (Power Distribution Network) impedance from supply current, voltage, and allowable ripple using Z_target = V_ripple / I_total. Recommends a ceramic bypass capacitor (high-frequency decoupling, placed closest to IC pins) and a bulk capacitor (low-frequency decoupling, near the regulator). Calculates the ceramic cap's self-resonant frequency assuming typical lead inductance, and checks whether ESR-induced ripple stays within limits. Essential for digital, analog, and mixed-signal PCB design. Chain with lc_resonance to verify the decoupling capacitor's resonant behavior, or with trace_width to size the power trace.

  ConnectorNo auth

• review_framework_codeA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  Scan source against known dead APIs (LLMChain, initialize_agent, ServiceContext, ripple-lib, …) and return each hit with replacement plus a unified-diff hunk. Use before running agent-written code; diagnose_framework_error is for after a stack trace. Does not execute or submit. Paid tools/call: $0.001 USDC or 1000 drops XRP; catalog-backed, not LLM-invented.

  ConnectorNo auth

• cut_rangeA

  MorphaReelsA

  Ripple-delete a time window [startFrame, endFrame) — remove that span and pull all later content earlier by delta = endFrame - startFrame (the NLE 'ripple delete' / 'close gap'). Shifts every keyframe, colour keyframe, marker, audio overlay, loop region, and start_at through the cut (a speed ramp is anchored to its clip and rides along unchanged), and is SOURCE-AWARE for video layers: a clip that straddles the cut is trimmed, and one whose interior is removed is SPLIT into two layers. Audio overlays interior to the cut are truncated at the seam (overlays have no source-in to bridge the gap). REFUSES to cut across a video layer that carries speed-ramp keyframes — remove them, or cut outside that layer's span, first. The composition length shrinks accordingly (an authored length loses only the overlap with its visible region). Frames are 0-indexed project-timeline frames at 30 fps; endFrame is exclusive and clamped to the composition length.

  Connector

  Destructive

  No auth

• enhance_cursorA

  Valmera — agentic AI video editorA

  PROJECT-SCOPED: this call acts only on the explicit project_id and returns the project identity with its result. MAKE THE MOUSE POINTER BIGGER AND STEADIER — THE tool for 'the cursor is too small' / 'too jittery' on a screen recording. It finds the pointer in the source frames, repaints the original out, and redraws it at `scale`x (1-4; 2 is the usual answer) along a path filtered to remove hand tremor — `smoothing` 0-1, where fast deliberate moves stay sharp at any setting. click_times is a list of SOURCE-video seconds that get an expanding ripple: I CANNOT see clicks in the pixels (nothing distinguishes a press from a hover), so either pass the times record_website_demo reported, or ask the user when the clicks were — never guess them. Set click_highlight=false to skip the ripples. This bakes into the source copy the render reads, so every cut keeps it and no timestamp moves; it reports what fraction of frames the pointer was actually found in and refuses outright on footage that has no visible cursor. Undo with remove_cursor_enhance.

  ConnectorOAuth

• get_fundA

  EventTrader MCPB

  One fund in full public detail: theme, mandate, direction, status, constituents where disclosed (short books aliased; open M&A baskets withheld), $ index price, % return since inception, profile / trade / invest URLs and focus areas. Symbol from list_funds (AIB symbols, or MA-RIPPLE, FTA-CRYPTOS, FTA-STOCKS, EVENT-CARD). Read-only, no auth.

  ConnectorNo auth

• get_fundA

  EventTrader Research (read-only)B

  One fund in full public detail: theme, mandate, direction, status, constituents where disclosed (short books aliased; open M&A baskets withheld), $ index price, % return since inception, profile / trade / invest URLs and focus areas. Symbol from list_funds (AIB symbols, or MA-RIPPLE, FTA-CRYPTOS, FTA-STOCKS, EVENT-CARD). Read-only, no auth.

  ConnectorNo auth

• add_keyframesA

  MorphaReelsA

  Add many keyframes to ONE element's ONE property in a single call, with an optional loop mode applied in the same call. The idiomatic form when every layer in a multi-element animation gets its own track (ripple dot pulse, snowflake fall, equaliser-bar wave). Factors elementId + property out of the loop body and folds set_track_loop in. Use set_keyframes_batch instead when you need to mix elements/properties in one atomic call.

  Connector

  Destructive

  No auth

• get_motion_recipesA

  StandoutA

  Production-ready motion for any stack: CSS/vanilla-JS recipes (staggered entrances, scroll reveals, marquees, grain, parallax) PLUS finished shader-grade ambient pieces - WebGL gradient mesh, image ripple displacement, live halftone, velocity-reactive type rail, scroll-scrubbed zoom portal - palette-keyed to Standout directions. Request by ids or describe what you need; pass direction for palette-filled shader code.

  ConnectorNo auth

• crypto_priceA

  LiveDataLinkB

  Get the current price and market data for any cryptocurrency. Returns price in USD, 24-hour change, market cap, volume, and all-time high. Use this for 'what's the price of bitcoin?', 'how much is ethereum?', 'solana price', 'check dogecoin', 'BTC price', 'ETH value', 'crypto price check', or any question about a specific coin's current value. Supports all major cryptocurrencies: bitcoin, ethereum, solana, cardano, ripple/XRP, dogecoin, polkadot, avalanche, chainlink, polygon/MATIC, litecoin, uniswap, stellar, cosmos, NEAR, arbitrum, optimism, aptos, sui, toncoin, shiba inu, pepe, BNB, tether/USDT, USDC, and thousands more via CoinGecko ID.

  ConnectorNo auth

• get_fund_history

  EventTrader MCPB

  Index history for one fund as [{t, v}] points, always including the fund's first (inception) point and its latest point — the whole history is evenly downsampled to fit, never a tail slice, so points[0].v matches get_fund's inception_index_price_usd — unless inception_at is set and pre_inception_points > 0: those leading points are the basket's pro-forma value before listing, and the inception point is the first one at/after inception_at (AIB funds: nominally-hourly writes, actual spacing varies; MA-RIPPLE: daily value of $100 at inception; FTA-CRYPTOS: 30-day daily closes, only on days every constituent has a venue price). FTA-STOCKS and EVENT-CARD have no history series — use get_fund for their current numbers. An empty series carries a note saying why. Read-only, no auth.

  ConnectorNo auth

• get_fund_history

  EventTrader Research (read-only)B

  Index history for one fund as [{t, v}] points, always including the fund's first (inception) point and its latest point — the whole history is evenly downsampled to fit, never a tail slice, so points[0].v matches get_fund's inception_index_price_usd — unless inception_at is set and pre_inception_points > 0: those leading points are the basket's pro-forma value before listing, and the inception point is the first one at/after inception_at (AIB funds: nominally-hourly writes, actual spacing varies; MA-RIPPLE: daily value of $100 at inception; FTA-CRYPTOS: 30-day daily closes, only on days every constituent has a venue price). FTA-STOCKS and EVENT-CARD have no history series — use get_fund for their current numbers. An empty series carries a note saying why. Read-only, no auth.

  ConnectorNo auth

• address_labels

  Bitquery: Crypto & Blockchain DataA

  Look up all known LABELS for a blockchain ADDRESS — entity, category, CEX deposit/hot wallet, mixer, gambling, scam, token-clone, contract type, NFT collection, ENS, … Works for both wallets and token/contract addresses. Use for "what / who is this address", "is this token a scam or a clone", "is this wallet a CEX or mixer". To label MANY addresses at once use `labels_for_addresses`; to list every address carrying a label use `addresses_by_label`; to resolve a human name to a stored value use `find_label_values`. Backed by the Bitquery address-label directory (directory.labels). Coverage: token/contract labels are dense on EVM (Ethereum, BSC, Polygon); exchange deposit / hot-wallet labels are broad on the EVM chains and Tron; wallet (EOA) labels are densest on Tron and Bitcoin; mixer labels exist essentially only for Bitcoin, and sanctioned / darknet tags sit mostly on Bitcoin, Tron and Ethereum. Pass chain='' (the default) to search every chain — recommended on EVM, where one address is the same owner on every chain and its label may be stored under a different one. Tracing note: MOST tracing rows carry NO label field, so this call is what puts a name on a counterparty. On Ethereum, BSC, Polygon, Arbitrum, Base, Optimism, Tron, the XRP Ledger, Stellar and Cardano NONE of the transfer / flow tools return a label — always look the address up here (or pass the whole counterparty list to `labels_for_addresses`). Only the Solana tools (address_flow_summary, flow_edges, trace_next_hop, transfers_in/out) and the Bitcoin-style tools of Bitcoin, Zcash, Litecoin, Dogecoin, Dash and Bitcoin Cash (address_profile, address_flow_summary, flow_edges, related_addresses, tx_flow) carry an inline label field at all, and even there it is SPARSE on Solana and EMPTY on every other chain (the inline list holds none of their addresses — batch those addresses into labels_for_addresses) — never treat a blank inline label as "unlabeled", always confirm it here. On the XRP Ledger (chain='ripple'), Cardano (chain='cardano'), Stellar (chain='stellar'), Litecoin (chain='litecoin') and Bitcoin Cash (chain='bitcoin-cash') the directory is sparse, mostly exchange reserve wallets; Dogecoin (chain='dogecoin') holds about 40,000 addresses, almost all exchange reserve wallets. Most Bitcoin Cash entries are stored in the old 1… / 3… address form, so a CashAddr (q… / p…) lookup finds only a few of them. Robinhood, Zcash, Dash and Arc have no label coverage at all, so an empty result there is a coverage gap, not a finding. An empty result while find_label_values shows rich coverage (e.g. 'binance') is a meaningful NEGATIVE signal, not missing data. One row per chain + label_type + label_value; recorded_at is the newest record of it. Several sources can record labels for one address. Rows that agree are merged: Sources lists every source behind a label and Source_Count how many there are. Labels that disagree stay separate — typically the same entity in different roles, e.g. cex-deposit-address AND cex-hot-wallet for one exchange, or a token-contract next to a token-clone. Such a conflict comes from different sources; weigh it by Source_Count and by the kind of source: sanctions lists (ofac, uk-ofsi, eu-sanctions …), official proof-of-reserves disclosures and verified sources are curated, while a source whose name contains "heuristic" was inferred from transfer patterns (broad, less certain) — trust the entity they agree on, and prefer the curated role when they differ. Source names: workflow:<name> is a Bitquery labelling pipeline - curated imports such as sanctions and issuer block lists, proof-of-reserves disclosures, research sets and label-provider enrichment - except that a name containing "heuristic" marks labels inferred from transfer patterns (most exchange-deposit labels); labels-query-service:<provider> was fetched on demand from an outside label provider when the address was looked up (one provider's view, not reviewed); a plain name is the dataset itself (ofac, uk-ofsi, eu-sanctions, japan-mof, france-gels and israel-nbctf are sanctions lists; walletexplorer and bitcoinabuse are public Bitcoin datasets), and a name containing "verified" is a reviewed import.

  ConnectorOAuth

• chain_describe_table

  Bitquery: Crypto & Blockchain DataA

  COLUMNS of one table in a per-chain transfer database — the DESCRIBE TABLE equivalent for eth_api, bsc_api, matic_api, arbitrum_api, base_api, optimism_api, robinhood_api, arc_api, tron_api, solana, bitcoin, bitcoin_flow, ripple, ripple_flow, cardano, cardano_flow, altcoin, altcoin_flow, bitcash, bitcash_flow and stellar: exact column name (case-sensitive), type, default kind and expression, comment, and whether the column is part of the sort key (filter on those first) or the partition key. Call it before writing SQL for <chain>_transfers_raw_sql: guessed column names fail, and the column sets differ between chains (tron has Transaction_FeePayer and no Transaction_From; solana, bitcoin and the other non-EVM databases use lower-case names). `table` is a name from chain_list_tables, e.g. transfers_sender, calls_to, events_tx, transfers_to, inputs_by_address; a "<database>." prefix is accepted. An EMPTY result means that database has no such table — call chain_list_tables. For trading_rt use describe_table.

  ConnectorOAuth

• chain_list_tables

  Bitquery: Crypto & Blockchain DataA

  TABLES of one per-chain transfer database (list the tables of eth, bsc, polygon, tron, solana, bitcoin …) — the SHOW TABLES equivalent for eth_api, bsc_api, matic_api (Polygon), arbitrum_api, base_api, optimism_api, robinhood_api, arc_api, tron_api, solana, bitcoin, bitcoin_flow, ripple / ripple_flow (XRP Ledger), cardano / cardano_flow, altcoin / altcoin_flow (Litecoin, Dogecoin and Dash in one database), bitcash / bitcash_flow (Bitcoin Cash) and stellar — with each table's engine, sort key, partition key and approximate row count (Total_Rows; empty for most solana, bitcoin, ripple, cardano, altcoin and stellar tables, where no quick count exists). Only the tables you should query are listed, under the name to use in SQL. The sort key is what makes raw SQL fast: filter on its LEADING columns first (e.g. the address of transfers_sender / transfers_receiver, the transaction hash of the *_tx tables); a query that skips them scans far more data and may time out. Next steps: chain_describe_table for one table's columns, chain_search_columns to find which table has a column, then that chain's <chain>_transfers_raw_sql to run the SQL (bitcoin and bitcoin_flow → btc_transfers_raw_sql, matic_api → matic_transfers_raw_sql, ripple* → xrp_transfers_raw_sql, cardano* → ada_transfers_raw_sql, altcoin* → ltc_ / doge_ / dash_transfers_raw_sql with the chain's blockchain_id filter, bitcash* → bch_transfers_raw_sql, stellar → xlm_transfers_raw_sql). Prefer a specialized per-chain tool whenever one answers the question — chain_capabilities lists them. For trading_rt (DEX trades, prices, OHLC bars) use list_tables; list_databases describes every database.

  ConnectorOAuth

• chain_search_columns

  Bitquery: Crypto & Blockchain DataA

  FIND COLUMNS by name inside one per-chain transfer database (eth_api, bsc_api, matic_api, arbitrum_api, base_api, optimism_api, robinhood_api, arc_api, tron_api, solana, bitcoin, bitcoin_flow, ripple, ripple_flow, cardano, cardano_flow, altcoin, altcoin_flow, bitcash, bitcash_flow, stellar) — which table has a column like "fee", "signature", "topic", "balance" or "prediction", with its exact name and type. `query` is a case-insensitive substring of the column name ("_" is literal), or a LIKE pattern when it contains % (e.g. "Transaction_%"); `table` optionally narrows the search to table names matched the same way (e.g. "events"). Returns at most 100 rows — exactly 100 means there are more, so narrow `query` or `table`. Then call chain_describe_table for the full column list of one table and <chain>_transfers_raw_sql to query it. Searches one database per call; for trading_rt use search_columns. Before hand-written SQL, check chain_capabilities: holders, contract calls and events, transaction history and flow tracing already have specialized tools.

  ConnectorOAuth

• find_currencies

  Bitquery: Crypto & Blockchain DataA

  Resolve a well-known asset by NAME or SYMBOL → Currency_Id, which aggregates every token of that asset across all chains. CALL THIS FIRST (then the currency_* tools) for well-known coins (USDC, USDT, WETH, WBTC, BTC, ETH, SOL, DAI, …) when the user has NOT pinned a chain or contract — currency-level aggregation gives a better price and wider coverage than any single token_* / pair_* query. Only fall back to find_tokens / token_* / pair_* when a specific chain ("USDC on Base") or contract is pinned. Discover currencies by name or symbol substring (case-insensitive) among those that traded in the last 24 hours. A "currency" is a coarser grouping than a token — e.g. `usdc` is one currency backed by many USDC tokens across chains; `bid:eth` is the native currency of Ethereum. Returns Currency_Id, Currency_Name, Currency_Symbol and 24h USD volume aggregated across all tokens of that currency. AGGREGATED CURRENCIES FIRST: `Is_Canonical` = 1 marks an aggregated currency — a named asset id (`usdc`, `doge`, `xrp`) or a chain's native coin (`bid:eth`, `bid:solana`, `bid:bitcoin`). Every other row (`bid:<chain>:<address>`) is ONE token that is mapped to no asset. Rows come in this order: aggregated currencies whose id, symbol or name equals the query; the other aggregated currencies; the other tokens; look-alikes last; USD volume decides inside each group. Is_Canonical says the id aggregates, not that it is the famous asset of that name: `bitcoin` is a meme token (Bitcoin is `bid:bitcoin`, whose supply and market cap count only the wrapped BTC on the indexed chains — do not report them as Bitcoin's), and one asset can have several ids (`trx` and `bid:tron`; `matic`, `pol` and `bid:matic`). NO ROW WITH Is_Canonical = 1 means the asset has no aggregated currency here — it is not covered, or it did not trade in the last 24 hours. The rows are then separate tokens that merely carry its name (bridged, wrapped or unrelated): say the asset is not covered and never quote such a row as the asset's price. canonical_only=1 returns the aggregated currencies alone. LOOK-ALIKES: `Symbol_Lookalike` = 1 means the token carries the symbol of an aggregated currency — `Lookalike_Of` names that currency (look-alike letters such as a Cyrillic `О` count as the same) — but is NOT part of it: never present it as that asset or use it for its price; call currency_price with the Lookalike_Of id instead. Tokens that merely share a common-word ticker (SUN, GOAT, …) with a currency are flagged too. `Matched_Via` = 'alias' marks an aggregated currency found because a token named exactly like the query, with at least $10,000 of USD volume in the last 24 hours, carries its symbol (e.g. "ripple" finds `xrp`); 'text' = its own name or symbol matched. `Symbol_NonAscii` = 1 flags a symbol that is not plain ASCII (normal for CJK / emoji names). `Volume_Usd_24h` is `null` when no volume is recorded at currency level — the case for the major USD stablecoins (usdc, usdt, dai, …). That is a gap of the aggregation, not a sign they are untraded; their tokens carry the volume (find_tokens). `Market_Cap_Usd` is circulating-supply based and is `null` when no circulating supply is known for the asset — normal for most long-tail assets, and not a sign the asset is untraded. `Fdv_Usd` (the total-supply valuation) is returned alongside it; label that number FDV, never "market cap", and treat a huge one with suspicion — supply that was minted and then parked on a burn address (`0x…dead`, `0x0`) still counts in the total supply behind it. `Fdv_Usd` is itself `null` when even the total supply is unknown — BOTH are null for an asset that carries no supply figures at this aggregated level, the case for several major stablecoins; resolve one contract with `find_tokens` and use `token_price` for a valuation then. Both are also WITHHELD (`null`, with a non-empty `Valuation_Warning`) when the supply or valuation behind them is implausible — report the valuation as unavailable. LONG NAMES: a name longer than 256 characters or a symbol longer than 64 is not searched (spam tokens that glue hundreds of asset names together). Returned names are cut at 128 characters and symbols at 32, ending in `…`; Name_Truncated / Symbol_Truncated = 1 marks a cut value.

  ConnectorOAuth

• list_databases

  Bitquery: Crypto & Blockchain DataA

  CATALOG of the databases raw SQL can reach — the SHOW DATABASES equivalent. For each database: what it holds, which tool runs SQL against it, how to see its tables, and which specialized tools answer the same questions without SQL. Call it before writing raw SQL against an unfamiliar database. Takes no parameters and answers instantly. trading_rt comes first: DEX trades, OHLC / volume bars, prices and supply for every trading chain over the last ~30 days — query it with execute_sql, browse it with list_tables, describe_table and search_columns. The per-chain databases (eth_api, bsc_api, matic_api, arbitrum_api, base_api, optimism_api, robinhood_api, arc_api, tron_api, solana, bitcoin, bitcoin_flow, ripple, ripple_flow, cardano, cardano_flow, altcoin, altcoin_flow - Litecoin, Dogecoin and Dash in one database, rows told apart by blockchain_id - bitcash, bitcash_flow for Bitcoin Cash, and stellar) hold transfers, calls, events, transactions and balances; browse them with chain_list_tables, chain_describe_table and chain_search_columns (pass the database name) and query each one with that chain's <chain>_transfers_raw_sql tool (xrp_, ada_, ltc_ / doge_ / dash_, bch_ and xlm_transfers_raw_sql for the ones above after bitcoin_flow). zcash and zcash_flow are queried with zec_transfers_raw_sql but the schema browser does not cover them: that tool's description lists their tables. stellar_flow is not browsable either - it starts in December 2023 and misses some ledgers, so query stellar instead. Address labels have no SQL access at all — use the label tools. Prefer a specialized tool whenever one answers the question: it already filters on the right keys and is far cheaper than hand-written SQL.

  ConnectorOAuth

• xrp_address_flow_summary

  Bitquery: Crypto & Blockchain DataA

  ADDRESS FLOW SUMMARY / top counterparties: who an XRP Ledger (xrp, XRP, ripple, XRPL) account pays and who pays it, in one call — profile (payments sent / received, distinct receivers / senders, tagged incoming payments) + TOP receivers AND TOP senders (ranked by number of payments then Σ amount). NOT only the statistics, without counterparties → use xrp_address_profile. Collapses address_profile + trace_next_hop(out) + an incoming convergence into a single call — call this FIRST when triaging a hop. Returns a computed Role over the same window and currencies as the profile counts (the last `days`, all currencies): receive_only (no outgoing payment in the window) / send_only (no incoming one) / no_transfers (neither) / hub (thousands of senders AND receivers — don't trace deeper) / consolidator (senders ≫ receivers) / distributor (receivers ≫ senders) / relay (neither dominates). An account paid mostly with destination tags (Tagged_Payments_Received close to Payments_Received) is a shared deposit account — an exchange or custodian — whatever its Role. Profile counts are all-currency; the top arrays honor currency, currency_id, issuer, min_amount and max_amount. The arrays carry NO labels: pass Address and the Top_Receivers / Top_Senders counterparties to labels_for_addresses(chain='ripple') in ONE call — it knows the reserve and proof-of-reserves accounts of the large exchanges (Binance's among them); coverage is otherwise sparse, so an empty answer is a coverage gap, not a clean account. For raw rows use xrp_transfers_in / xrp_transfers_out. READING THE TOP ARRAYS: positional 6-tuples [counterparty, amount, currency, currency_id, payments, tagged_payments] (the Top_Fields column lists these names in the same order), one entry per (counterparty, currency) — the same address repeats once per currency it moved. tagged_payments > 0 on a receiver = you paid a shared deposit account (exchange) with destination tags. ONLY PAYMENTS between two different accounts are counted; value moved by an account deletion, check, escrow, payment channel, AMM or NFT sale has no recorded counterparty and is not in the arrays (see Type=other in xrp_transfers_in / xrp_transfers_out). Failed transactions never count. CURRENCY: native XRP is currency_id 413663; any other currency_id is a currency CODE that look-alike issuers reuse — pin the real token with currency_id plus issuer (receivers: the token this account sent; senders: the token this account received). Amounts here are TOKEN UNITS, never USD - no USD value is available in this data, so there is no usd filter and totals for different currencies must not be compared or added together. For a ranking you can reason about, pin ONE currency with currency_id, or bound the range with min_amount / max_amount. Counts and rankings cover the LAST 90 DAYS by default, not the account's whole lifetime; raise days for a longer period. Window_Days / Window_From on the row state the period actually covered: an account busy long ago but quiet since comes back all zeros - raise days.

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• xrp_address_profile

  Bitquery: Crypto & Blockchain DataA

  XRP Ledger (xrp, XRP, ripple, XRPL) account STATISTICS — payments sent / received, distinct receivers / senders, how many incoming payments carried a destination tag and how many different tags, other value records (account deletions, checks, escrows, AMM, NFT legs), filled exchange offers, transactions signed (successful and failed) and fees paid (Fees_Paid_XRP, in XRP - fees are always paid in XRP), first / last activity. Triage an account during tracing. Role from the ratios: senders ≫ receivers = consolidator / sweep; receivers ≫ senders = distributor; ~1↔1 = relay (layering); thousands of both = hub (exchange / service — don't trace deeper). Tagged_Payments_Received close to Payments_Received with many Distinct_Destination_Tags = a shared deposit account (exchange, custodian). Failed_Transactions far above the successful ones = an automated bot. NOT who it deals with → use xrp_address_flow_summary. Counts cover the LAST 90 DAYS by default, not the account's whole lifetime; raise days for a longer period. Window_Days / Window_From on the row state the period actually covered: an account that was busy long ago but quiet since comes back all zeros, which is NOT the same as an account that never moved anything - raise days to look further back. No USD values; for labels use labels_for_addresses(chain='ripple').

  ConnectorOAuth

• xrp_flow_edges

  Bitquery: Crypto & Blockchain DataA

  MONEYFLOW GRAPH EDGES out of an XRP Ledger (xrp, XRP, ripple, XRPL) account: Source → Target, total Amount, Currency, Currency_Id, payment count and how many of them carried a destination tag. NOT choosing which counterparty to follow next → use xrp_trace_next_hop. Building block for a MoneyFlow DIAGRAM — call per address/hop, collect edges, render Mermaid `graph LR`, flag & stop at exchange / service nodes (the edges carry no labels — identify targets with labels_for_addresses(chain='ripple') in one call; a target receiving tagged payments is a shared deposit account, typically an exchange). Edges are ranked by number of payments then amount. Pin a currency with currency_id to avoid dust and spam tokens; time-window the edges with after_time / before_time. An edge carries the currency that LEFT the source: a cross-currency payment shows only the sent side (what the target received is in xrp_transfers_in of the target), and a conversion into another currency inside one account (a payment to itself) is not an edge at all — to spot an off-ramp, call WITHOUT a currency filter and compare the currencies of consecutive hops. For raw rows use xrp_transfers_out. ONLY PAYMENTS between two different accounts form edges. Value moved by an account deletion, check, escrow, payment channel, AMM or NFT sale has no recorded target on its sending leg, so it is NOT an edge here — open such transactions (Type=other in xrp_transfers_out) with xrp_tx_transfers (an escrow or payment channel pays out in a later, separate transaction). Failed transactions never count. CURRENCY: native XRP is Currency_Id 413663; any other Currency_Id is a currency CODE that look-alike issuers reuse — pin the real token with currency_id plus issuer (matched on the token that left the source). Amounts here are TOKEN UNITS, never USD - no USD value is available in this data, so there is no usd filter and totals for different currencies must not be compared or added together. For a ranking you can reason about, pin ONE currency with currency_id, or bound the range with min_amount / max_amount. Counts and rankings cover the LAST 90 DAYS by default, not the account's whole lifetime; raise days for a longer period.

  ConnectorOAuth

• xrp_trace_dominant_path

  Bitquery: Crypto & Blockchain DataA

  AUTO-WALK the dominant (largest total amount) OUTGOING PAYMENT edge of ONE currency from an XRP Ledger (xrp, XRP, ripple, XRPL) account, hop by hop, up to 5 hops — collapses ~5 manual xrp_trace_next_hop calls into one. Follows native XRP by default (currency_id 413663). Every hop returns Hop*_To (the account that received), Hop*_Edge_Total, Hop*_Transfers and Hop*_Tagged_Transfers (how many of those payments carried a destination tag), plus Hops_Found and Path_Status for the walk itself. Hop*_Edge_Total is NOT the amount that travelled along the path: it is the total of EVERY payment of that currency between that hop's sender and receiver over the whole window (days, counted back from today on every hop), so it can be far larger than the sum you are tracing and the hop totals are not comparable with each other. For one hop's full ranking call xrp_trace_next_hop on the hop's sender. The walk NEVER goes back to an account it has already visited (the seed included), and by default it STOPS at an account that was paid with destination tags: that is a shared deposit account, typically an exchange, and its onward payments are the service's own movements, not the traced funds (Path_Status EXCHANGE_DEPOSIT; stop_at_tagged=0 walks on). READ Path_Status FIRST — NO_MATCH means no outgoing payment of this currency in the window (wrong currency_id, or raise days), PATH_END means the trail really ran out, DEPTH_LIMIT means it may continue past hop 5. The walk carries no labels: pass the hop accounts to labels_for_addresses(chain='ripple') in one call and read down to the first labeled account. ONLY PAYMENTS count: value that left through an account deletion, check, escrow, payment channel, AMM or NFT sale is not followed. currency_id identifies a currency CODE, which look-alike issuers reuse, and the walk does not separate issuers — for an issued token check each hop with xrp_trace_next_hop and its issuer filter; a hop INTO the token's issuer means the tokens were redeemed. Amounts are in the currency's own units (XRP, not drops), never USD. LIMITS: follows only the single biggest edge per hop (misses splits / fan-outs), fixed depth 5. For branching tracing call xrp_trace_next_hop hop by hop and choose the next account yourself (prompt_playbook with playbook=money_flow returns the full procedure). A multi-hop walk over busy accounts can take several seconds; lower days, or raise min_amount to step over dust edges.

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