# citepath

**Canonical:** https://apis.io/providers/citepath-ai/  
**Website:** https://citepath.ai/  
**APIs profiled:** 1

Citepath provides Generative Engine Optimization (GEO) services to help brands track and improve how AI search engines cite, mention, and recommend them. The platform audits technical signals such as llms.txt, JSON‑LD, robots.txt, sitemaps, and feeds, offering a 14‑day free trial and tiered plans for comprehensive AI SEO insights.

## Kin Score — 22.1 / 100 (emerging)

Scored 2026-11-06 under rubric 0.27.0.

| Facet | Score |
|---|---|
| Discoverability | 66.1 |
| Contract Quality | 0.0 |
| Contract Governance | 4.5 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 21.9 |
| Access Clarity | 53.9 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 13.6 (matched via fallback).

## Agent readiness — 4.7 (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 | unknown |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | flavored |
| 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

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

## APIs (1)

- **citepath API** — Track and optimize how AI search engines cite, mention, and recommend your brand.

## Security (1)

- **Citepath Ai Domain Security** — TLSv1.3 · HSTS · DMARC

## Plans (1)

- **Citepath Ai Plans Pricing**

## Tags

Artificial Intelligence, SEO, Optimization, Analytics, Company

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