# Autokz

**Canonical:** https://apis.io/providers/autokz/  
**Website:** https://www.autokz.com  
**APIs profiled:** 0

Autokz, operating as Aoto Technology Co., Ltd., is a heavy‑machinery enterprise based in Kazakhstan that designs, manufactures, and services drilling equipment for water‑well, geological exploration, and engineering borehole applications. The company offers a broad product line including multi‑functional top‑drive drilling rigs, crawler‑mounted rigs, wireline coring rigs, and specialized drilling solutions for mining, energy, water‑conservation and municipal engineering projects worldwide.

## Kin Score — 4.0 / 100 (minimal)

Scored 2026-11-02 under rubric 0.26.0. Trend: flat (+0.0 from 4.0).

| Facet | Score |
|---|---|
| Discoverability | 53.6 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Access Clarity | 0.0 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 5.9 (matched via fallback).

## 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 |
| Delegated Identity | no |
| Protected Resource Metadata | no |
| Dynamic Client Registration | no |
| Agentic Commerce | no |
| Pagination Ratio | na |
| Operation Distinctiveness | na |
| MCP Tool Quality | na |

## Access

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

## Security (1)

- **Autokz Domain Security** — TLSv1.3 · HSTS

## Tags

Heavy Machinery, Drilling Equipment, Kazakhstan, Industrial Engineering, Water Well

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