Execution
How AI agents buy APIs
A practical guide to the discovery, policy, payment, execution, and receipt loop that lets AI agents buy API access without a manual account handoff.
TL;DR
In Weft’s recommended architecture, an AI agent buys API access by turning its task into a capability request, finding compatible providers, comparing available terms, obtaining policy approval, satisfying the provider’s payment challenge, retrying the request with payment evidence, and recording both the result and settlement evidence.
What to remember
- The purchase begins with a required capability, not a vendor name.
- Price is only one ranking signal; fit, freshness, latency, and reliability also matter.
- Policy approval should happen before credentials or payment are released.
1. Translate the task into a capability
Suppose an agent is asked to find ten fintech companies in Zurich and verify the CTO’s working email at each company. The task contains at least two distinct capabilities: current company discovery and contact enrichment. A robust agent should not assume one provider can do both well.
The agent expresses each requirement in machine-readable terms: geographic scope, industry, role, freshness, confidence threshold, maximum latency, and budget. This capability description becomes the basis for search and evaluation.
2. Search and rank the available services
A discovery layer can return services that declare the required capability. Where reliable first-party observations exist, Weft’s ranking model can combine declared metadata with measured response time, failures, freshness, and outcomes from consented routed calls.
The preferred option is contextual rather than universally “best.” Provenance, freshness, latency, price, and output quality can carry different weights for different tasks. Advertised terms and measured behavior must remain separate evidence.
4. Return the result, receipt, and outcome signal
Protocol evidence has a narrower scope than a Weft execution record. x402’s core response reports settlement, while MPP can return a payment receipt. Neither proves that the API output was correct or useful. Weft enriches that evidence with provider identity, endpoint, quoted and settled amounts, policy decision, and measured result.
Where Weft has legitimate first-party outcome data, it can improve future routing: whether the API returned usable data, whether it was fresh enough, and whether another provider had to repair the result. Transaction evidence becomes a ranking signal only after it is separated from and then joined to capability and outcome context.
Sources and further reading
Protocols change quickly. We reviewed the primary sources below on July 23, 2026.