# Moonhub

**Canonical:** https://apis.io/providers/moonhub/  
**Website:** https://moonhub.ai  
**APIs profiled:** 0

Moonhub is an AI recruiting platform that deploys proprietary AI agents to source, qualify, engage, and vet candidates across millions of profiles, helping companies hire faster and more cost-effectively. Its agent products (Qualify AI, Engage AI, and Monitor AI) automatically identify qualified candidates, run outreach to convert them into interview-ready applicants, and analyze candidate intent to manage recruiter handoffs. Moonhub is backed by Khosla Ventures, GV, Greycroft, Time Ventures, and AIX Ventures; the Moonhub team joined Salesforce in 2026. The company ships a recruiter web application (recruiter.moonhub.ai) and publishes no public developer API, SDK, or documentation surface as of this profiling.

## Kin Score — 10.5 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 10.5).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Commercial Clarity | 27.6 |
| Access Clarity | 27.6 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **Moonhub Domain Security** — TLSv1.3 · HSTS · DMARC

## Tags

Company, Artificial Intelligence, Recruiting, Talent Acquisition, Hiring, AI Agents, HR Tech, Sourcing

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/moonhub/). Scores are computed from the provider's own public artifacts under a published rubric.