AgentReady gives any website an MCP server, llms.txt and cited answers for AI agents. Free plan available, paid plans from $49/month. Read the review.
Researched and fact-checked by Bartu Cavusoglu · Updated October 26, 2026
AgentReady is an agent interface platform that makes a website easier for AI agents to read and query. A site owner pastes a public URL, and the service builds a structured layer on top of the existing site: a hosted MCP server, a generated llms.txt file and an endpoint that returns cited answers.
The problem it targets is familiar to anyone who has asked an AI assistant about a product. According to the company, agents that rely on plain web fetching often get empty content from JavaScript-rendered sites, fetch only one page when an answer spans several, and return no citations. AgentReady's pitch is to fix those three failures without changing the original site.
The company was founded by Ashutosh Raj and lists 2026 as its founding year. It serves two groups: site owners who want assistants to answer correctly about their product, and agent developers who want one endpoint for querying many sites.
After you sign in and paste a URL, AgentReady crawls and indexes the site. The pipeline has four layers: it uses llms.txt or llms-full.txt if the site already publishes one, runs a standard HTML crawl through the sitemap or links, extracts embedded data from Next.js apps, and falls back to the Jina Reader service for JavaScript-only pages. The company says a typical site takes about 60 seconds.
Once indexed, the site gets an MCP endpoint, llms.txt, a capability manifest and a REST ask endpoint. When someone asks a question, the system embeds the query, retrieves matching chunks from a vector index and passes them to Claude Sonnet 4.6, which is told to cite each claim by source URL.
Every crawl produces a changelog diff, and a content scanner hash-pins pages and removes text that looks like prompt injection before it reaches the answer prompt. Owners can keep the index current by running a refresh command from CI after each deploy.
The core feature set is available on the Free plan: a public MCP endpoint, llms.txt generation, cited answers, an agent-readiness grade and seven days of analytics. The analytics show agent visits, tool calls, success rate and latency, and a separate view reports visits from AI products such as ChatGPT, Perplexity, Claude, Gemini and Copilot.
Pro adds tools aimed at quality control. The Agent Simulator scores a site on five representative agent tasks. Query gap detection lists questions the index could not answer confidently and drafts content briefs for site owners to fill in with real facts. Answer tests check live answers against expected facts, and GitHub check runs fail a build when answers regress.
Trust features include fact attestation, where owners mark extracted facts such as pricing as verified so they come first in every answer, and an agent registry that labels known agents in analytics. Private MCP access locks an endpoint behind an API key for internal content.
AgentReady is an agent interface platform. You paste a public URL, and it crawls the site, generates llms.txt, and hosts an MCP server and a cited question-answering endpoint. AI clients such as Claude Desktop, Cursor and Windsurf can then query the site.
The Free plan is $0. Pro costs $49 per month and Team costs $149 per month, billed monthly in USD. Enterprise pricing is custom and handled through the enterprise page.
Yes. Free covers one site, up to 100 pages, five index refreshes per month, the public MCP endpoint, llms.txt generation, cited answers, an agent-readiness grade and 7-day analytics. No credit card is required.
Its crawl pipeline includes a Jina Reader fallback that renders JavaScript-only sites, and it parses embedded data for Next.js apps. The company's benchmark reports 76% fact coverage on JS-heavy sites versus 56% for web_fetch.
It works with MCP-compatible clients including Claude Desktop, Cursor, Windsurf and VS Code Copilot. On Pro it posts GitHub check runs and sends Slack regression alerts. A REST endpoint is also available for non-MCP use.
No code is required to index a site. You sign in, paste a URL and the endpoint is generated. An optional script tag adds browser agent discovery and analytics, and developers can use the CLI or REST API.
It suits SaaS and documentation site owners who want AI assistants to answer accurately about their product, and agent developers who want cited answers from any website through one MCP endpoint.
Yes. You can cancel from the dashboard and keep access until the end of the billing period. Plans are billed monthly through Dodo Payments.