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The Data API is a single, standardized REST interface to the data behind Intel: onchain activity, market and asset coverage, protocol and sector fundamentals, and the curated metrics our analysts use in production. Every endpoint is read-only, served from https://api.blockworks.com, authenticated with one API key, and returns the same { "error": ..., "data": ... } envelope, so a client written against one product area works against all of them. Endpoints come in two model kinds. Tabular models are row-shaped: entities, rankings, and current metrics you filter, sort, and page through. Timeseries models are history-shaped: a metric over time for a given entity, at a granularity you choose in the path.

Quickstart

Get a key and make your first authenticated request in under five minutes.

Tabular vs timeseries

The two model kinds, their URL shapes, and when to reach for each.

Filtering & pagination

Filter operator suffixes, sorting, column selection, paging, and response formats.

The data catalog

The API describes itself: enumerate every model, column, filter, and granularity.

Finding an id

Which lookup table gives the series key each timeseries endpoint needs.

Reference

Every model with its columns, metrics, examples and errors, grouped by subject. Start with Market Data.

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Request shape

Tabular endpoints live under /query/tabular/<model>, optionally with an entity identifier. Timeseries endpoints live under /query/timeseries/<model>/<granularity>.
Every request carries the key in the X-Blockworks-API-Key header. See Authentication. The <model> segment is the model’s catalog slug. A few older slugs keep working as aliases and resolve to the same endpoint: asset-entities for assets, network-entities and networks for the tabular blockchains model, network and networks for the timeseries one. The reference documents the canonical slug only.

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What you can build

  • Dashboards and terminals: asset, protocol, and sector screens backed by research-grade metrics rather than scraped aggregates.
  • Quant and research pipelines: reproducible timeseries pulls with explicit granularity and point-in-time semantics.
  • Enrichment services: resolve symbols, slugs, and identifiers to canonical entities before joining Blockworks metrics onto your own records.

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Next steps

Responses

The envelope, the tabular row shape, and the timeseries series shape.

Errors

Status codes, the error envelope, and how to resolve common failures.

Granularity

Choosing an interval and bounding a time window.
Need more than a REST endpoint should reasonably return? The same models are available natively in your warehouse through Datashares.