# InfoAddict

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

InfoAddict is a personal brand and consultancy focused on AI, product, and technology. Through a portfolio of experiments, showcases, and writings, Dan Crane shares insights on applied AI, conversational products, and strategic technology implementation. The site features a blog, project showcases, a newsletter, and resources like llms.txt, reflecting a blend of thought leadership and practical development work.

## Kin Score — 8.5 / 100 (minimal)

Scored 2026-11-13 under rubric 0.28.0.

| Facet | Score |
|---|---|
| Discoverability | 58.3 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 2.4 |
| Access Clarity | 17.0 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 7.3 (matched via fallback).

## Agent readiness — 6.3 (agent-aware)

| 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 | yes |
| 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)

- **InfoAddict MCP Server** — Remote MCP server at infoaddict.com.

## Security (1)

- **InfoAddict Domain Security** — TLSv1.3 · HSTS · DNSSEC · DMARC

## Tags

Artificial Intelligence, Product, Technology, Consultancy, PersonalBrand

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