# AtlasClose

**Canonical:** https://apis.io/providers/atlasclose-com/  
**Website:** https://atlasclose.com/  
**APIs profiled:** 0

AtlasClose MCP is an experimental governance layer for AI agents, providing authorization, enforcement, and audit recording of agent actions. It offers a controlled environment where AI agents begin with no authority and must request permissions, with decisions logged in a hash‑chained record for tamper detection. The platform is experimental, not production‑certified, and uses synthetic data for demonstrations.

## Kin Score — 10.1 / 100 (minimal)

Scored 2026-11-06 under rubric 0.27.0. Trend: flat (-4.4 from 14.5).

| Facet | Score |
|---|---|
| Discoverability | 48.2 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 2.6 |
| Developer Ergonomics | 11.9 |
| Access Clarity | 10.5 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 18.2 (matched via fallback).

## Agent readiness — 2.5 (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 | documented |
| 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

Open access — onboarding: open, pricing: unknown, trial: no (confidence: low).

## Security (2)

- **Atlasclose Com Authentication** — 0 schemes
- **Atlasclose Com Domain Security** — TLSv1.3 · DMARC

## Tags

Artificial Intelligence, Governance, Experimental, MCP, Control

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