# Cybergenic

**Canonical:** https://apis.io/providers/cybergenic-im/  
**Website:** https://cybergenic.im/  
**APIs profiled:** 0

Cybergenic is an autonomous cancer research engine that reasons across cancer genomics, drugs, clinical trials, and scientific literature in real time. It generates cited hypotheses, shows its computational work, and aims to accelerate oncology discoveries by integrating vast biomedical data sources into a coherent, interactive platform for researchers and clinicians.

## Kin Score — 9.2 / 100 (minimal)

Scored 2026-11-06 under rubric 0.27.0.

| Facet | Score |
|---|---|
| Discoverability | 48.3 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 2.4 |
| Access Clarity | 21.1 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 12.7 (matched via fallback).

## Agent readiness — 3.5 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | documented |
| 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).

## MCP servers (1)

- **Cybergenic MCP Server** — Remote MCP server at cybergenic.im.

## Security (1)

- **Cybergenic Im Domain Security** — TLSv1.3 · HSTS · DMARC

## Tags

Artificial Intelligence, Oncology, Genomics, Data Integration, Research Platform

---

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