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Run402 Hobby Tier Subscriptionx402$5/message
api.run402.comRunbot StratForge Quick Strategyx402$3.99/message
mcp.runbot.ioRuneSwap x402 Airdrop Registrationx402$0.1/message
runeswap.comRuneSwap Bitcoin Transaction & Address Queryx402$0.001/message
dogui.vercel.appRuneSwap x402 Airdrop Registrationx402$0.1/messagedogui.vercel.appRuneSwap Rune Minterx402$4/messagedogui.vercel.appRunMyData DryScout01 Hellox402$0.001/message
runmydata.comRyze Agent - deBridge Cross-Chain Quotex402$0.002/message
api.ryzeagent.xyzRyze Agent - DeBridge Yield Migration Analyticsx402$0.005/messageapi.ryzeagent.xyzSableForge Text Analysis APIx402$0.0005/message
sableforge.servehttp.comsadf (df) - x420.dev: Buy 1 USDC of df Tokensx402$1/message
df.x420.devSYNTHORA safe_to_tradex402$0.03/message
safe-to-trade.hergertsynthora.comSampled Geometric Observing Window - Celestial Visibilityx402$0.100013/message
mahastrategies.comSampled-Series Integration via Composite Trapezoidal Rulex402$0.018501/messagemahastrategies.comSampling Observations — Adjacent Row Changes + Base-100 Seriesx402$0.01/message
market.datapackvibe.comSampling Observations — Adjacent Row Changes + Date-by-Category Pivotx402$0.01/messagemarket.datapackvibe.comSampling Observations — Adjacent Row Changes + Equal-Width Histogramx402$0.01/messagemarket.datapackvibe.comSampling Observations — Adjacent Row Changes + Explicit Missing-Value Fillx402$0.01/messagemarket.datapackvibe.comSampling Observations — Adjacent Row Changes + Keyed Dataset Comparisonx402$0.01/messagemarket.datapackvibe.comSampling Observations — Adjacent Row Changes + Secondary-Measure Weighted Meanx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics: Adjacent Row Changes + Two-Measure Correlationx402$0.01/messagemarket.datapackvibe.comSampling Observations Base-100 Series and Explicit Missing-Value Fillx402$0.01/messagemarket.datapackvibe.comSampling Observations Base-100 Series and Keyed Dataset Comparisonx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics: Category Frequencies + Adjacent Row Changesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Category Frequencies + Base-100 Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Category Frequencies + Daily Sum Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Category Frequencies + Equal-Width Histogramx402$0.01/messagemarket.datapackvibe.comSampling Observations — Category Frequencies + Explicit Missing-Value Fillx402$0.01/messagemarket.datapackvibe.comSampling Observations — Category Frequencies + Numeric Interval Filterx402$0.01/messagemarket.datapackvibe.comSampling Observations — Category Frequencies + Numeric Row Orderingx402$0.01/messagemarket.datapackvibe.comSampling Observations — Category Frequencies + Secondary-Measure Weighted Meanx402$0.01/messagemarket.datapackvibe.comSampling Observations — Category Frequencies + Trailing Mean Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations Daily Sum Series and Adjacent Row Changes Analyticsx402$0.01/messagemarket.datapackvibe.comSampling Observations — Daily Sum Series + Date by Category Pivotx402$0.01/messagemarket.datapackvibe.comSampling Observations — Daily Sum Series + Equal-Width Histogramx402$0.01/messagemarket.datapackvibe.comSampling Observations Daily Sum Series with Missing-Value Fillx402$0.01/messagemarket.datapackvibe.comSampling Observations — Daily Sum + Secondary-Measure Weighted Meanx402$0.01/messagemarket.datapackvibe.comSampling Observations — Daily Sum Series + Trailing Mean Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations Daily Sum Series and Two-Measure Correlationx402$0.01/messagemarket.datapackvibe.comSampling Observations Date-by-Category Pivot with Missing-Value Fillx402$0.01/messagemarket.datapackvibe.comSampling Observations — Date-by-Category Pivot + Keyed Dataset Comparisonx402$0.01/messagemarket.datapackvibe.comSampling Observations — Duplicate Key Report + Adjacent Row Changesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Duplicate Key Report + Base-100 Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations Duplicate Key Report and Category Frequenciesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Duplicate Key Report + Equal-Width Histogramx402$0.01/messagemarket.datapackvibe.comSampling Observations — Duplicate Key Report + Grouped Numeric Summaryx402$0.01/messagemarket.datapackvibe.comSampling Observations — Duplicate Key Report + Numeric Interval Filterx402$0.01/messagemarket.datapackvibe.comSampling Observations — Duplicate Key Report + Numeric Row Orderingx402$0.01/messagemarket.datapackvibe.comSampling Observations — Duplicate Key Report + Secondary-Measure Weighted Meanx402$0.01/messagemarket.datapackvibe.comSampling Observations — Duplicate Key Report + Trailing Mean Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Equal-Width Histogram + Date by Category Pivotx402$0.01/messagemarket.datapackvibe.comSampling Observations — Equal-Width Histogram + IQR Outlier Flagsx402$0.01/messagemarket.datapackvibe.comSampling Observations — Equal-Width Histogram + Keyed Dataset Comparisonx402$0.01/messagemarket.datapackvibe.comSampling Observations — Equal-Width Histogram + Secondary-Measure Weighted Meanx402$0.01/messagemarket.datapackvibe.comSampling Observations — Exact Row Deduplication + Adjacent Row Changesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Exact Row Deduplication + Base-100 Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Exact Row Deduplication + Daily Sum Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Exact Row Deduplication + Duplicate Key Reportx402$0.01/messagemarket.datapackvibe.comSampling Observations — Exact Row Deduplication + Explicit Missing-Value Fillx402$0.01/messagemarket.datapackvibe.comSampling Observations — Exact Row Deduplication + IQR Outlier Flagsx402$0.01/messagemarket.datapackvibe.comSampling Observations — Exact Row Deduplication + Numeric Distributionx402$0.01/messagemarket.datapackvibe.comSampling Observations — Exact Row Deduplication + Trailing Mean Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics — Grouped Numeric Summary + Adjacent Row Changesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Grouped Numeric Summary + Base-100 Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Grouped Numeric Summary + Explicit Missing-Value Fillx402$0.01/messagemarket.datapackvibe.comSampling Observations — Grouped Numeric Summary + IQR Outlier Flagsx402$0.01/messagemarket.datapackvibe.comSampling Observations — Grouped Numeric Summary + Keyed Dataset Comparisonx402$0.01/messagemarket.datapackvibe.comSampling Observations — Grouped Numeric Summary + Trailing Mean Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations IQR Outlier Flags and Date-by-Category Pivotx402$0.01/messagemarket.datapackvibe.comSampling Observations IQR Outlier Flags + Keyed Dataset Comparisonx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Distribution + Adjacent Row Changesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Distribution + Base-100 Series Analyticsx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics — Numeric Distribution + Date by Category Pivotx402$0.01/messagemarket.datapackvibe.comSampling Observations Numeric Distribution and Missing-Value Fillx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Distribution + Grouped Numeric Summaryx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Distribution + Keyed Dataset Comparisonx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Distribution + Numeric Interval Filterx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Distribution + Numeric Row Orderingx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Distribution + Secondary-Measure Weighted Meanx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Distribution + Trailing Mean Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Distribution + Two-Measure Correlationx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Interval Filter + Adjacent Row Changesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Interval Filter + Base-100 Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Interval Filter + Daily Sum Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Interval Filter + Date by Category Pivotx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Interval Filter + Equal-Width Histogramx402$0.01/messagemarket.datapackvibe.comSampling Observations Numeric Interval Filter and Keyed Dataset Comparisonx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Interval Filter + Trailing Mean Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Row Ordering + Base-100 Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Row Ordering + IQR Outlier Flagsx402$0.01/messagemarket.datapackvibe.comSampling Observations — Numeric Row Ordering + Two-Measure Correlationx402$0.01/messagemarket.datapackvibe.comSampling Observations — Record Quality Audit + Daily Sum Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations — Record Quality Audit + Exact Row Deduplicationx402$0.01/messagemarket.datapackvibe.comSampling Observations — Record Quality Audit + Exact Row Deduplication + Adjacent Row Changesx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics: Record Quality Audit + Exact Row Deduplication + Base-100 Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics — Record Quality Audit + Exact Row Deduplication + Category Frequenciesx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics: Record Quality Audit + Exact Row Deduplication + Daily Sum Seriesx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics — Record Quality Audit + Exact Row Deduplication + Equal-Width Histogramx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics — Quality Audit, Deduplication & Grouped Summaryx402$0.01/messagemarket.datapackvibe.comSampling Observations Analytics: Record Quality Audit + Exact Row Deduplication + Numeric Distributionx402$0.01/messagemarket.datapackvibe.com
Sets a user to the hobby tier ($5.00 USDC) on Run402, auto-detecting whether this is a new subscription, renewal, or upgrade
Builds, optimizes, and exports a crypto trading strategy based on user-defined parameters, monetized via x402 micropayment.
Registers a Bitcoin address to receive the x402 airdrop on Bitcoin Ordinals via RuneSwap.
Query Bitcoin transaction and address data on-demand for verification and tracking.
Registers a Bitcoin address for the x402 airdrop on Bitcoin Ordinals
Mints a specified Bitcoin Rune directly to a given Bitcoin address on mainnet.
Performs a paid x402 connectivity check on Base mainnet, returning a simple status:ok response for $0.001 USDC per call.
Fetches cross-chain bridge quotes via deBridge with AI-generated actionable insights and confidence scores on Solana DeFi
Returns AI-interpreted analytics and actionable signals for yield migration opportunities via deBridge on Solana DeFi
Analyzes a text string and returns byte count, character count, line count, and word count statistics.
Purchases exactly 1 USDC worth of df tokens (0x3077c5e15F8BD67F05f73b4dC49a507543FF0b07) on-chain and returns transaction details
Returns a pre-trade go/no-go safety verdict for a given trade input via a signed x402 micropayment call.
Computes deterministic approximate GMST-based celestial geometry (altitude/visibility) for a set of UTC time samples, an observer site, and frozen equatorial target positions, without refraction or live atmospheric data.
Numerically integrates 2–128 equally spaced integer samples using the composite trapezoidal rule, returning an exact rational result with declared units and an integrity receipt.
Computes adjacent row-to-row changes and a base-100 indexed series for up to 200 sampling observation records with sample values and weights.
Runs two local analytical reports on supplied sampling observation rows: an adjacent-row change analysis and a date-by-category pivot table.
Computes two analytical reports on sampling observation data: sequential adjacent-row changes and an equal-width histogram, for up to 200 rows.
Computes adjacent row changes and fills missing values (zero, mean, or median) for up to 200 rows of weighted sampling observation data, returning 2 analytical reports.
Analyzes up to 200 sampling observation rows (sample_value, sample_weight) producing two reports: adjacent row change analysis and keyed dataset comparison between two supplied datasets.
Computes adjacent row-to-row changes and secondary-measure weighted mean for up to 200 supplied sampling observation records in a single call.
Computes adjacent row changes and two-measure correlation for up to 200 supplied sampling observation records (sample_value, sample_weight) in two independent reports.
Computes a base-100 index series and fills missing values (zero, mean, or median) for up to 200 rows of weighted sampling observation data.
Computes a Base-100 indexed time series and a keyed dataset comparison report for up to 200 rows of weighted sampling observations.
Analyzes supplied sampling observation rows to produce two reports: category frequency distributions and adjacent row change metrics, using local analytical engines with no external lookups.
Computes category frequency distributions and a base-100 index series from user-supplied weighted sampling observation records
Analyzes supplied sampling observation records to produce two reports: category frequency distributions and daily sum time series, using local analytical engines.
Computes category frequency counts and an equal-width histogram for up to 200 sampling observation records (sample_value, sample_weight).
Computes category frequencies and fills missing values (zero, mean, or median) for up to 200 weighted sampling observation records, delivering two analytical reports in one call.
Computes category frequency distributions and numeric interval filtering for sampling observation records (sample_value, sample_weight) across up to 200 rows, returning two analytical reports per call.
Analyzes up to 200 sampling observation records to produce two reports: category frequency counts by dataset group and numeric row ordering by a chosen field (sample_value or sample_weight).
Computes category frequencies and secondary-measure weighted mean for up to 200 user-supplied sampling observation rows (sample_value, sample_weight) using local analytics.
Computes category-frequency distributions and trailing moving-average series for up to 200 weighted sampling observation records in a single call.
Computes two analytical reports for sampling observation data: a daily sum series and adjacent row changes, across up to 200 rows of sample_value/sample_weight records.
Computes two analytical reports from supplied sampling observation rows: a daily sum time series and a date-by-category pivot table, for up to 200 rows.
Computes a daily sum time series and an equal-width histogram from supplied sampling observation records (sample_value, sample_weight) for up to 200 rows.
Computes daily sum series and fills missing values (zero, mean, or median) for up to 200 sampling observation records with sample_value and sample_weight fields.
Computes a daily sum time series and a secondary-measure weighted mean for up to 200 supplied sampling observation records (sample_value, sample_weight).
Computes a daily sum series and a trailing mean series from supplied sampling observation rows (with sample_value and sample_weight), returning two analytics reports for up to 200 rows.
Computes a daily sum time series and a two-measure correlation report for up to 200 sampling observation records with sample_value and sample_weight fields.
Pivots supplied sampling observation rows (sample_value or sample_weight) by date and category, then fills missing values using zero, mean, or median imputation — returning two analytical reports for up to 200 rows.
Runs two analytical reports on supplied sampling observation records: a date-by-category pivot table and a keyed dataset comparison between two datasets, for up to 200 rows.
Analyzes up to 200 sampling observation rows to produce two local analytical reports: a duplicate key report and an adjacent row changes report for a selected numeric field.
Generates a duplicate key report and a base-100 index series for up to 200 rows of sampling observation records (sample_value, sample_weight).
Analyzes up to 200 sampling observation rows to produce two local reports: a duplicate key report and category frequency distribution for sample_value and sample_weight fields.
Analyzes up to 200 sampling observation records (sample_value, sample_weight) to produce a duplicate key report and an equal-width histogram in a single API call.
Analyzes up to 200 sampling observation rows to produce two reports: a duplicate key report and a grouped numeric summary for sample_value or sample_weight fields.
Runs two local analytical reports on supplied sampling observation rows: a duplicate key report and a numeric interval filter, for up to 200 rows of sample_value/sample_weight data.
Analyzes supplied sampling observation records to produce a duplicate key report and a numeric row ordering report for up to 200 rows.
Runs two local analytical reports on supplied sampling observation rows: a duplicate key report and a secondary-measure weighted mean calculation.
Analyzes up to 200 sampling observation rows to produce a duplicate key report and a trailing (rolling) mean series for a chosen numeric field.
Generates two analytical reports (equal-width histogram and date-by-category pivot) from up to 200 supplied sampling observation records with sample_value and sample_weight fields.
Computes an equal-width histogram and IQR-based outlier flags for up to 200 sampling observation records (sample_value or sample_weight).
Generates an equal-width histogram and a keyed dataset comparison report for up to 200 sampling observation records (sample_value, sample_weight).
Computes an equal-width histogram and a secondary-measure weighted mean over up to 200 supplied sampling observation records (sample_value, sample_weight).
Deduplicates exact rows and detects adjacent row changes in supplied sampling observation records (sample_value, sample_weight) for up to 200 rows.
Deduplicates exact rows and computes a Base-100 indexed series for up to 200 sampling observation records (sample_value or sample_weight).
Deduplicates exact rows and computes daily sum time series for up to 200 sampling observation records with sample_value and sample_weight fields.
Deduplicates sampling observation records by exact row match and generates a duplicate key report, processing up to 200 rows with two analytical reports per call.
Deduplicates exact rows and fills missing values in sampling observation records (sample_value, sample_weight) for up to 200 rows, returning 2 analytical reports.
Deduplicates exact duplicate rows and flags IQR-based outliers in sampling observation records with sample_value and sample_weight fields, producing two analytical reports per call.
Runs two local analytical reports on supplied sampling observation records: exact row deduplication and numeric distribution analysis for up to 200 rows.
Deduplicates exact rows and computes trailing mean series for user-supplied sampling observation records (sample_value, sample_weight) across up to 200 rows.
Computes two analytical reports on supplied sampling observation rows: a grouped numeric summary (by dataset_group) and adjacent row-to-row change analysis, for up to 200 rows of sample_value/sample_weight data.
Computes a grouped numeric summary and a base-100 index series from supplied sampling observation records (sample_value, sample_weight) for up to 200 rows.
Computes grouped numeric summary statistics and fills missing values (zero, mean, or median) for up to 200 sampling observation rows with sample_value and sample_weight fields, returning two analytical reports.
Computes grouped descriptive statistics and IQR-based outlier flags for up to 200 sampling observation records with sample_value and sample_weight fields.
Computes a grouped numeric summary and a keyed dataset comparison for up to 200 sampling observation rows (sample_value, sample_weight), returning two analytical reports per call.
Computes a grouped numeric summary and a trailing mean series for up to 200 sampling observation records with sample values and weights.
Runs two local analytical reports on supplied sampling observation rows: IQR-based outlier flagging and a date-by-category pivot table.
Runs two local analytical reports on sampling observation records: IQR-based outlier flagging and keyed dataset comparison, for up to 200 rows at $0.01 USDC.
Analyzes up to 200 sampling observation rows (sample_value/sample_weight) producing two local analytical reports: a numeric distribution summary and an adjacent row change analysis.
Computes numeric distribution statistics and a base-100 indexed series for up to 200 user-supplied weighted sampling observation rows, returning two analytical reports.
Analyzes up to 200 sampling observation rows to produce two local reports: a numeric distribution summary and a date-by-category pivot table, using sample_value or sample_weight as the target field.
Computes numeric distribution statistics and fills missing values (zero, mean, or median) for up to 200 weighted sampling observation rows, returning two analytical reports.
Computes a numeric distribution report and a grouped numeric summary for up to 200 weighted sampling observation rows, returning two local analytical reports for a single $0.01 USDC fee.
Analyzes up to 200 sampling observation rows (sample_value, sample_weight) to produce two reports: a numeric distribution analysis and a keyed dataset comparison between two supplied datasets.
Computes a numeric distribution analysis and a numeric interval filter report for up to 200 weighted sampling observation records.
Computes numeric distribution statistics and numeric row ordering for up to 200 supplied sampling observations (sample_value, sample_weight) in two independent analytical reports.
Computes numeric distribution statistics and secondary-measure weighted mean for up to 200 supplied sampling observation records (sample_value, sample_weight).
Computes a numeric distribution report and a trailing mean time series for up to 200 weighted sampling observation records supplied by the caller.
Computes a numeric distribution analysis and a two-measure correlation report for up to 200 sampling observation records (sample_value, sample_weight) using local analytical engines.
Applies a numeric interval filter and adjacent row change analysis to supplied sampling observation records (sample_value, sample_weight) for up to 200 rows, returning 2 analytical reports.
Applies a numeric interval filter and computes a base-100 index series on up to 200 supplied sampling observation rows (sample_value, sample_weight), returning two analytical reports.
Filters sampling observation rows by a numeric interval and computes a daily sum time series, returning two analytical reports for up to 200 supplied rows.
Filters sampling observation records by a numeric value range and produces a date-by-category pivot table, returning two analytical reports for up to 200 rows.
Filters sampling observation records by a numeric interval and computes an equal-width histogram over up to 200 rows, returning two analytical reports in one call.
Runs two local analytical reports on user-supplied sampling observation rows: a numeric interval filter and a keyed dataset comparison across up to 200 records.
Filters sampling observation rows by a numeric interval and computes a trailing mean series over user-supplied sample data, returning two analytical reports for up to 200 rows.
Computes numeric row ordering and a base-100 index series for up to 200 supplied sampling observation records with sample_value and sample_weight fields.
Analyzes supplied sampling observation records by ordering rows numerically and flagging outliers using the interquartile range (IQR) method, producing two analytical reports for up to 200 rows.
Analyzes up to 200 sampling observation rows by computing numeric row ordering and two-measure correlation between sample_value and sample_weight fields.
Audits data quality and computes daily sum time series for up to 200 sampling observation rows containing sample_value and sample_weight fields.
Performs a two-report local analysis on up to 200 sampling observation rows: a record quality audit and exact row deduplication, using only supplied data with no external lookups.
Runs three local analytical reports on sampling observation rows: record quality audit, exact row deduplication, and adjacent row change detection for sample_value or sample_weight fields.
Runs three local analytical reports on up to 200 sampling observation rows: a record quality audit, exact row deduplication, and a base-100 index series for sample_value or sample_weight.
Runs three local analytical reports on sampling observation records: a record quality audit, exact row deduplication, and category frequency analysis — all on up to 200 rows of sample_value/sample_weight data.
Runs three independent analytical reports on sampling observation records: a record quality audit, exact row deduplication, and daily sum series computation, for up to 200 rows.
Runs three local analytical reports (record quality audit, exact row deduplication, and equal-width histogram) on up to 200 sampling observation records with sample_value and sample_weight fields.
Runs three analytical reports on sampling observation data: a record quality audit, exact row deduplication, and a grouped numeric summary — all in a single call for up to 200 rows.
Runs three local analytical reports on up to 200 sampling observation rows: a record quality audit, exact row deduplication, and numeric distribution analysis for sample_value or sample_weight.