Underscore launches 20+ APIs for AI agents and developers

The _done suite addresses a fundamental limitation in how AI systems operate: large language models excel at generating human-like text but are unreliable at deterministic, verifiable tasks. When an AI model is asked to compute a cryptographic hash or check whether a domain is registered, it cannot actually perform those operations—it can only produce text that resembles the correct answer. In production systems, this leads to silent failures, broken security checks, and corrupted data integrity. By packaging 20+ utility APIs under a single service, _done offers AI agents and developers a way to outsource these operations to reliable endpoints that always return the same result for the same input.

The APIs span three broad categories: network and domain infrastructure (ASN lookup, DNS/WHOIS, domain age, domain availability, ENS resolution, port scanning, HTTP headers); security and cryptography (CORS checking, hashing and HMAC verification); and data fetching (Hacker News scraping, OCR from images, HTTP requests). Several APIs explicitly acknowledge the hallucination problem—the JSON suite handles the common case where an AI model's JSON output is slightly malformed, and the hash-hmac tool uses timing-safe comparison to prevent secret-leaking attacks that might occur if an untrusted signature check were left to a language model.

The architecture appears designed for integration into AI agent workflows: each API accepts structured input (a domain name, an IP address, a JSON string) and returns deterministic output (status codes, record data, parsed text). Bulk operations reduce the number of requests needed to process many items at once. This lowers latency and cost for applications that rely on AI agents to orchestrate multiple data lookups or network checks as part of a larger task.