SEO and marketing decision
Reaudit
A capable developer can replicate a meaningful subset (audits, schema fixes, basic tracking and publishing) in ~36 hours, but Reaudit's MCP server, broad multi-agent integrations and enterprise analytics are hard to fully reproduce.
Visit website↗$50/mo
$600/yr
Read off the official pricing page.
$100one-off36 h to build
$50/mo6 h/mo upkeep
On cash alone, building overtakes the subscription at 2 seats.
No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- Crawl and audit a website for AI-readiness, monitor AI-engine citations for tracked queries, generate citation-optimized content, and publish/patch site schema and robots/llms files.
What it still won’t have
- The prebuilt MCP server with 197 agent tools and one-key agent integrations
- Broad built-in connectors and platform coverage (many AI engines, publishing targets, paid intelligence)
- White-label, dedicated support, enterprise features and long-term data retention tiers
- Production-grade analytics dashboards and anomaly alerting across many ad platforms
What remains hard
- Integration maintenance
197 tools · 1 API key · Any MCP client
- Brand trust
50+ Brands Trust Reaudit
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 2 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a self-hosted AI-visibility microservice (Node.js + Next.js frontend, Postgres, Redis for jobs, deployed on a single AWS t3.small EC2 or equivalent). Core features in scope: 1) site crawler that fetches and parses HTML, extracts metadata and existing JSON-LD; 2) an audit engine that scores AI-readiness and produces prioritized fixes; 3) a simple citation tracker that queries/scrapes 3 AI-overview endpoints (ChatGPT/Perplexity/Gemini via their public interfaces or HTTP scraping) and stores citation events; 4) an LLM integration using OpenAI to generate articles with JSON-LD and suggested robots/llms changes; 5) WordPress publishing via REST API and a small scheduler for recurring visibility checks. Out of scope: multi-engine MCP server, 197 tool integrations, enterprise billing, white-labeling, and paid-ad intelligence. Include error handling, retries for network jobs, authentication for a single admin user, unit tests for crawl/parser and audit scoring, and a basic end-to-end integration test for publish workflow.
How we checked
How the score was reached
- Partly verdict base52
- 3 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Evidence score62
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 3
Every page the run actually retrieved.
- official productReaudit — official product
- official pricingReaudit Pricing — Starter €50 /mo
- official docsReaudit MCP — 197 AI Tools for Your Agent
Integrity checks
What held up, and what did not.
