All Services

Fetches open interest data for a given trading symbol from a self-hosted financial data endpoint

Returns all SPL token accounts held by a given Solana wallet address

Generates a personalized birthday message for a named person based on their relationship to the sender

Looks up the current SOL balance for a given Solana wallet address

Decodes a hex-encoded cryptographic signature into its constituent components

Generates a dashboard layout or configuration from a natural language description

Search for cryptocurrency coins by name or symbol query string

Generates a JSON Schema definition from a provided JSON example or description string

Returns the current Bitcoin (BTC) price, likely in USD, from a self-hosted endpoint priced per call via crypto micropayment.

Extracts named entities (people, places, organizations, etc.) from a given text string, returning a structured array of identified entities.

Generates a formatted pricing page for a given product, optionally with named tiers and prices.

Returns the total token supply for a given contract address on a specified EVM-compatible blockchain network

Returns current fiat currency exchange rates for a given currency code

Generates authentication scaffolding code for a given tech stack with specified auth providers (e.g. email, Google, GitHub).

Looks up detailed information about a cryptocurrency by its ID

Looks up transaction signatures associated with a given Solana wallet address

Returns current price or quote data for a given stock ticker symbol

Returns the current Crypto Fear & Greed Index score and sentiment classification for the market.

Generates a themed pickup line based on a user-specified theme using self-hosted AI inference.

Returns the current perpetual futures funding rate for a given trading symbol

Fetches live PyPI package metadata and health information for the FastAPI Python package (or any specified package).

Returns live PyPI source repository and documentation URLs for the FastAPI Python package (or any specified package).

Returns OSV security advisory fixed-version boundaries for a given version of the fastify npm package

Retrieves install lifecycle hook metadata for the fastify npm package from the registry, useful for integration and upgrade planning.

Returns module and type entrypoints from npm registry metadata for the fastify package, useful for integration and upgrade planning.

Returns runtime and platform compatibility constraints for the fastify npm package, including engine requirements, OS support, and integration metadata for upgrade planning.

Lists available macroeconomic data sources powering the Fathom API, which provides access to 816,000+ FRED economic time series

Evaluates vendor/supplier risk before a payment is made, returning a GO/NO-GO decision with confidence score based on IBAN, company name, email, domain, country, currency, and invoice amount.

Screens a supplier or counterparty by IBAN, name, email, domain, country, currency, and invoice amount, returning a GO/NO-GO decision with confidence level for prepayment gating.

Screens a name against restricted party lists and returns a verdict indicating whether the name requires review based on match count.

Runs two analytical reports on feature availability records — adjacent row change detection and a date-by-category pivot — for up to 200 rows of populated vs. expected feature data.

Runs two local analytical reports on feature availability data: adjacent row-to-row change detection and an equal-width histogram, for up to 200 rows.

Analyzes feature availability records to produce two reports: adjacent row change detection and explicit missing-value fill, using local analytical engines on up to 200 rows.

Analyzes feature availability records (populated_features, expected_features) to detect adjacent row changes and flag IQR-based outliers across up to 200 rows, producing two independent analytical reports.

Computes adjacent row change analysis and two-measure correlation for feature availability data (populated_features vs expected_features) across up to 200 rows.

Computes Base-100 index series and IQR-based outlier flags for feature availability data (populated_features, expected_features) across up to 200 rows, delivering two independent analytical reports.

Computes a Base-100 indexed series and a keyed dataset comparison for supplied feature availability records (populated_features vs expected_features) across up to 200 rows.

Computes a Base-100 index series and a secondary-measure weighted mean for feature availability records (populated_features vs expected_features) over up to 200 rows.

Analyzes feature availability records to produce two reports: category frequency distributions and adjacent row changes, for up to 200 rows of populated/expected feature data.

Computes category frequency distributions and a base-100 indexed series for feature availability records (populated_features vs expected_features) across up to 200 rows.

Computes two analytical reports (category frequencies and daily sum series) for up to 200 feature availability records defined by populated_features and expected_features fields.

Computes two local analytical reports — category frequency distribution and date-by-category pivot table — for supplied feature availability records (populated_features, expected_features).

Computes category frequency counts and an equal-width histogram for populated_features or expected_features columns across up to 200 feature availability records.

Computes category-level frequency distributions and IQR-based outlier flags for up to 200 feature availability records (populated_features or expected_features), returning two independent analytical reports.

Analyzes feature availability records to produce two reports: category-level frequency distributions and a keyed comparison between two datasets (rows vs other), covering populated vs expected feature counts across up to 200 rows.

Computes category frequencies and applies a numeric interval filter on supplied feature availability records (populated_features / expected_features) for up to 200 rows, returning two independent analytical reports.

Analyzes feature availability records to produce two reports: category frequency distributions and trailing mean time series, for up to 200 rows of populated/expected feature data.

Runs two analytical reports on feature availability data: a daily sum time series and adjacent row change detection, for up to 200 rows of populated/expected feature counts.

Computes two analytical reports — a daily sum time series and a date-by-category pivot table — from supplied feature availability records (populated_features and expected_features) for up to 200 rows.

Computes a daily sum time series and flags IQR-based outliers for feature availability data (populated_features and/or expected_features) across up to 200 supplied rows.

Analyzes feature availability records by computing a daily sum time series and a keyed dataset comparison across up to 200 rows, returning two independent analytical reports.

Computes daily sum series and trailing mean series for feature availability records (populated_features and expected_features) from user-supplied row data, returning two analytical reports in one call.

Runs two analytical reports on feature availability data: a date-by-category pivot table and a keyed comparison between two datasets, for up to 200 rows.

Generates two local analytical reports—a duplicate key report and a base-100 index series—for supplied feature availability records (populated_features and expected_features) across up to 200 rows.

Generates two offline analytical reports — a duplicate key report and a daily sum series — for supplied feature availability records (populated_features, expected_features) across up to 200 rows.

Generates two local analytical reports — a duplicate key report and a date-by-category pivot — for supplied feature availability records (populated_features, expected_features) across up to 200 rows.

Runs two local analytical reports on feature availability data: a duplicate key report and an equal-width histogram, for up to 200 rows of populated/expected feature counts.

Runs two local analytical reports on feature availability records: a duplicate key audit and an explicit missing-value fill using zero, mean, or median imputation, for up to 200 rows.

Analyzes up to 200 feature availability records to produce two reports: a duplicate key report and a grouped numeric summary across populated_features and expected_features fields.

Analyzes up to 200 feature availability records to produce a duplicate key report and IQR-based outlier flags for populated_features or expected_features values.

Analyzes up to 200 feature availability records to produce two independent reports: a duplicate key report and a numeric distribution for populated_features or expected_features.

Analyzes up to 200 feature availability records to produce two local reports: a duplicate key report and a numeric interval filter on populated_features or expected_features.

Generates two local analytical reports — an equal-width histogram and a date-by-category pivot table — for supplied feature availability (populated_features, expected_features) records, up to 200 rows.

Computes an equal-width histogram and applies explicit missing-value fill on feature availability records (populated_features, expected_features) for up to 200 rows, returning 2 analytical reports.

Computes an equal-width histogram and a two-measure Pearson/linear correlation for supplied feature availability records (populated_features vs expected_features) in a single paid call.

Performs exact row deduplication and adjacent row change detection on feature availability records (populated_features, expected_features) for up to 200 rows, returning two independent analytical reports.

Runs exact row deduplication and a base-100 indexed series report on up to 200 feature availability records (populated_features vs expected_features) using local analytical engines.

Deduplicates exact rows and computes a daily sum time series for feature availability records (populated_features and expected_features) across up to 200 rows.

Performs exact row deduplication and date-by-category pivot analysis on supplied feature availability records (populated_features, expected_features) for up to 200 rows.

Runs two local analytical reports on feature availability records: exact row deduplication and duplicate key detection, for up to 200 rows per call.

Analyzes feature availability records by performing exact row deduplication and generating an equal-width histogram on populated_features or expected_features values, returning two independent analytical reports for up to 200 rows.

Deduplicates exact duplicate rows and generates a grouped numeric summary report for feature availability records (populated_features, expected_features) across dataset groups and dates.

Deduplicates feature availability records and flags IQR-based outliers for populated_features or expected_features columns across up to 200 rows.

Performs exact row deduplication and keyed dataset comparison on two sets of feature availability records (populated_features vs expected_features), returning two independent analytical reports for up to 200 rows.

Performs exact row deduplication and numeric distribution analysis on up to 200 feature availability records (populated_features, expected_features) using local analytical engines.

Performs exact row deduplication and trailing mean series analysis on feature availability records (populated_features, expected_features) for up to 200 rows.

Runs two local analytical reports on feature availability data: a grouped numeric summary by dataset group and an adjacent row change analysis, for up to 200 rows at once.

Computes a grouped numeric summary and a Base-100 indexed time series from supplied feature availability records (populated_features vs expected_features) for up to 200 rows.

Computes a grouped numeric summary and category frequency distribution for feature availability data (populated_features and expected_features) across up to 200 rows, using local analytical engines.

Computes a grouped numeric summary and a daily sum time series for feature availability data (populated_features, expected_features) across up to 200 rows, returning two local analytical reports.

Computes a grouped numeric summary and fills missing values for feature availability records (populated_features, expected_features) across up to 200 rows.

Computes a grouped numeric summary and a keyed dataset comparison for supplied feature availability records (populated_features vs expected_features) across up to 200 rows.

Computes a grouped numeric summary and a trailing mean time series for feature availability records (populated_features, expected_features) from up to 200 supplied rows.

Computes a grouped numeric summary and a two-measure correlation report for feature availability records (populated_features, expected_features) across up to 200 rows.

Analyzes feature availability records to produce IQR-based outlier flags and a date-by-category pivot table for up to 200 rows of populated/expected feature data.

Runs IQR-based outlier detection and two-measure correlation analysis on supplied feature availability data (populated_features vs expected_features) for up to 200 rows.

Analyzes feature availability records (populated_features, expected_features) to produce two reports: a numeric distribution histogram and an adjacent row change analysis, for up to 200 rows.

Computes a numeric distribution report and a base-100 indexed time series for supplied feature availability data (populated_features vs expected_features) across up to 200 rows.

Computes numeric distribution statistics and category frequency breakdowns for feature availability records (populated_features and expected_features) across up to 200 rows.

Computes numeric distribution statistics and daily sum time series for feature availability data (populated_features, expected_features) across up to 200 rows, returning two independent analytical reports.

Runs two local analytical reports on supplied feature availability data: a numeric distribution summary and a date-by-category pivot, for up to 200 rows.

Computes numeric distribution statistics and fills missing values (zero, mean, or median) for feature availability records across up to 200 rows, producing two independent analytical reports.

Computes numeric distribution statistics and IQR-based outlier flags for up to 200 feature availability records across two independent analytical reports.

Computes a numeric distribution report and a keyed dataset comparison for up to 200 feature availability records (populated_features vs expected_features) using local analytical engines.

Computes a numeric distribution and numeric interval filter report for up to 200 feature availability records (populated_features, expected_features), returning 2 analytical reports per call.

Computes numeric distribution statistics and row ordering reports for feature availability records (populated_features, expected_features) across up to 200 rows, returning two independent analytical reports.

Computes a numeric distribution report and a trailing mean time series for feature availability data (populated_features and expected_features) supplied by the caller, using local analytical engines with no external lookups.

Computes numeric distribution statistics and Pearson correlation between populated_features and expected_features for up to 200 supplied feature-availability records in two independent reports.

Analyzes feature availability records by filtering rows within a numeric interval and detecting adjacent row changes across populated_features or expected_features fields.

Runs two local analytical reports on feature availability data: filters rows by a numeric interval and produces a daily sum time series for populated_features or expected_features.