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AgentReady
Crawls any docs site and serves it to agents as a hosted MCP endpoint, llms.txt and cited answers
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https://agentready.it.com
About AgentReady
AgentReady is an interface layer that makes a documentation site queryable by AI agents. The problem it states is concrete: agents trying to use your docs parse raw HTML, miss a large share of the pages, and then hallucinate answers about your product. AgentReady crawls a site you nominate, indexes it, and gives it three things agents can actually consume — a hosted MCP endpoint they connect to immediately, a spec-compliant llms.txt at the site root that agents discover without any code change, and a capability manifest. Queries return cited answers: exact quotes with source URLs rather than a generated paragraph, so an agent's response is grounded in your actual content. Setup is claimed at under a minute with no code — sign in with Google, paste a URL, and the crawler indexes the pages (the demo shows 218 pages indexed and the MCP endpoint live). The second half of the product is the feedback loop: agent analytics show which agents are querying your docs and what they are asking, and query gap detection surfaces the questions your content does not answer. Paid tiers add an agent simulator that scores your site on five tasks, GitHub check runs on every refresh so a docs change that breaks agent answers fails CI, and Slack regression alerts. There is also a free grade report for measuring where a site stands before committing, and a public directory of indexed sites.
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Key Features
AgentReady Pros & Cons
✅ Pros
- +Free tier is a working product for one site, not a trial
- +CI check runs turn docs quality into a gate rather than a periodic audit
- +llms.txt plus MCP covers both the passive and active discovery paths
⚠️ Cons
- −Free tier's MCP endpoint is public, so private docs need Pro
- −100-page free crawl limit is small for real documentation
- −Counting subdomains as separate sites pushes multi-domain setups up a tier
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Alternatives to AgentReady
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