Documentation
Everything you need to build with AuditMe: the REST API, the MCP server that lets AI agents run live SEO audits, the full audit methodology, and the machine-readable knowledge surfaces used by search engines and AI answer engines.
SEO Didn't Die. Websites Got Harder to Understand. — the 2026 guide to SEO, GEO, AI search visibility and website intelligence, built from the same evidence this documentation describes.
Quick Start
Run a full SEO audit with a single HTTP request. No key. Just a URL.
curl "https://www.auditme.dev/api/v1/audit?url=https://example.com"
const res = await fetch("https://www.auditme.dev/api/v1/audit?url=https://example.com");
const data = await res.json();
console.log("Score:", data.score, "| Grade:", data.grade);import requests
r = requests.get("https://www.auditme.dev/api/v1/audit", params={"url": "https://example.com"})
print(r.json()["score"])Documentation library
Direct HTTP access: run SEO audits, AI visibility scans and retrieve machine-readable JSON responses. No API key required.
Connect Claude, Cursor, Windsurf and other AI agents over the Model Context Protocol. 14 tools with zero-friction public read access.
Step-by-step config to connect Claude Desktop to AuditMe via streamable-http MCP transport.
Connect Perplexity to AuditMe's MCP server so AI search can run live audits.
How AuditMe scores websites: 159 checks across 15 categories, weighting, severity logic, data sources and limitations.
Legacy interactive API docs with request examples and response formats.
Product guides, troubleshooting and the technical SEO framework explainer.
Evidence-first research on SEO, GEO, AI search visibility and the 2026 state of SEO — with reproducible methodology.
Live AI visibility tracking: how AI answer engines see and cite websites across the ecosystem.
Machine-readable surfaces for AI agents
Search engines, RAG pipelines, LLM crawlers and AI answer engines discover AuditMe through these structured endpoints. Keep them linked from any integration.
Key endpoints
| Endpoint | Method | Purpose |
|---|---|---|
| /api/v1/audit | GET | Full SEO audit (159 checks across 15 categories) |
| /api/ai-visibility-scan | POST | AI visibility & AI readiness check |
| /api/mcp | POST | MCP protocol endpoint (14 tools) |
Integrate AuditMe
Use AuditMe as a building block: automate SEO reporting, feed audits into CI/CD pipelines, or let AI agents diagnose and fix websites over MCP. The API returns deterministic JSON — audit results and fix suggestions are data-driven, not LLM-generated, so you can trust them in automation.
curl https://www.auditme.dev/.well-known/mcp.json
curl -X POST https://www.auditme.dev/api/mcp \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'Frequently asked questions
Does the AuditMe API require an API key?
No. The public API is open to everyone — no signup or API key required. Read-only MCP tools (get_site_info, get_audit_methodology, get_seo_concept) also work without authentication. Authenticated MCP tools like seo_audit accept an optional x-api-key header to raise limits. This keeps the barrier to entry at zero: any agent, bot, or analyst that can reach https://www.auditme.dev/api/v1 can produce a full report in seconds without provisioning credentials first.
How do AI agents connect to AuditMe?
AI agents connect over the Model Context Protocol (MCP 2026-07-28). Point any MCP-compatible client (Claude Desktop, Cursor, Windsurf, Perplexity) at https://www.auditme.dev/api/mcp and the agent can list and call the exposed audit tools. Discovery metadata is at https://www.auditme.dev/.well-known/mcp.json.
How many checks are in an AuditMe audit?
A full AuditMe audit runs 159 checks across 15 categories. Each check produces a pass/warn/fail result with evidence, grouped by category and severity, then weighted into a 0-100 composite score with a grade.
Can I audit a website by crawling only its URL?
Yes. Pass any public URL to the audit endpoint (https://www.auditme.dev/api/v1/audit?url=...) or use the seo_audit MCP tool. AuditMe fetches the page, runs the full check registry, and returns a structured JSON report with prioritized fixes.
Where can I read the full documentation for AI systems?
The /docs page is the human-readable hub. For machine-readable knowledge, AI systems should start with /llms.txt, /llms-full.txt, /openapi, and /.well-known/agent-card.json. Research methodology is published at /research and referenced from blog posts.
Field guides from the AuditMe blog
Deep, evidence-first guides that complement the documentation — the same material AI answer engines cite most often.