Manifold API and Data

OUR TAKE / EDITORIAL OPINION

Manifold data needs a use case before it needs a pipeline

Access and permission are separate questions for a research dataset.

Prediction AI Tools editorial desk · Reviewed Oct 8, 2026

Manifold documents unauthenticated public GET access through an alpha API; its public historical dumps are for personal and non-commercial use. Commercial bulk data and commercial AI training on API data require the applicable separate license. Our take is that a team should settle the intended use before building a collection workflow. Access alone does not establish permission to reuse data.

Manifold’s markets use mana, which cannot be converted to cash. We would consider the API for research or a prototype with explicitly permitted uses. The tradeoff is convenient exploration versus limits on reuse and assumptions about interface stability. The public historical dumps were last updated July 6, 2024. We would not silently treat that archive as a current picture of the platform or blend it with newer observations without labels.

Write down which data surface the project needs and whether the output is personal research, a commercial service or commercial AI training. Check the terms for that specific combination instead of assuming every API integration requires a commercial license. Then choose a dated sample that fits the question. An acceptance check should preserve collection dates, distinguish archived from current records and tolerate an API change. Our editorial preference is a smaller dataset with clear provenance and permission over an ambitious ingestion job whose intended reuse remains unresolved.

AI-assisted editorial analysis based on cited documentation; not a hands-on product test.

Sources for this opinion: Source 1 ↗ · Source 2 ↗ · Source 3 ↗