Map the human surface.
Arachne scans authorized pages, links, forms, docs, metadata, structured data, and policy pages to build a normalized capability model.
The web was built for human eyeballs, which makes it hostile to AI agents. Arachne compiles any authorized website into an evidence-backed Shadow API: a live MCP endpoint, normalized capabilities, domain verification, artifact version history, capability-token governance, Agent Run Validation traces, drift monitoring, reports, and a tamper-evident audit ledger. Sites keep their existing web surface; agents get a safe interface.
"Describing a dashboard you can't see is exactly what Arachne is going to change."
Arachne evaluates how an AI agent sees your site, where each usable capability came from, what actions it can infer, and which workflows need structured resources, action contracts, domain verification, approval boundaries, or policy gates.
Arachne scans authorized pages, links, forms, docs, metadata, structured data, and policy pages to build a normalized capability model.
Generate llms.txt, agent-manifest.json, MCP resources, normalized capability artifacts, an evidence map, and a risk-classified action registry.
Identify writes, forms, checkout paths, auth surfaces, and prompt-injection risks before agents treat untrusted page content as instructions.
Arachne runs bounded browser-agent tasks against your public website to prove whether agents can understand your offer, find pricing, choose the right contact path, identify trust signals, and stop safely before write actions. Every run produces task traces, failure points, and fixes.
Do the machine-readable signals exist: MCP, OpenAPI, llms.txt, sitemap, robots, JSON-LD, and semantic forms?
Can Arachne normalize the public surface into agent-facing resources, tools, evidence, risk, and policy?
Can a bounded agent actually complete buyer tasks on the site, explain failures, and stop before writes?
The output is not a scraper report. It is a repeatable interface layer that tells agents what exists, where each capability came from, what they can read, what they can draft, what changed since the last compile, and what needs approval before execution.
A verified domain enters the bounded crawler. External, private, and disallowed routes stay outside scope.
Server-rendered sites get the fast HTML crawl. JS SPAs route to a headless-Chromium pipeline that renders each page and observes the real fetch/XHR traffic — so the resulting Shadow API gets the actual API endpoints, methods, and request shapes, not empty action="" forms.
Read actions, draft actions, submit actions, purchases, auth paths, and inferred workflows are normalized with source mode, source URL, confidence, risk, approval requirement, and evidence.
Arachne keeps the runtime manifest as the agent contract while emitting normalized capability, evidence, risk, and versioned artifact history for reports, bundles, drift monitoring, and customer review.
Normal validation proves whether agents can complete buyer tasks. Safety boundary testing checks whether approval gates, form-use limits, page-instruction handling, and risky-action controls hold under realistic agent behavior.
The full deliverables now live on their own page. The short version: Arachne ships the machine interface, evidence, governance runtime, domain verification, artifact diffs, dashboard, reports, and customer bundle needed to make a site agent-ready.
Agents get structured tools and resources instead of brittle browser automation.
Every capability carries source, confidence, risk level, approval rules, domain-verification state, and a recommended default access policy.
Operators can review readiness, tools, actions, audit logs, drift alerts, artifact diffs, and customer reports.
A 0-100 agent-readiness score, in seconds, no signup. If you like what you see, the full report is $49 — billed instantly via Stripe — and lands you on a live preview of the Shadow API we'd build for your domain.