CanAgentUse

CanAgentUse products

MCP ServerInstall CanAgentUse in your coding agent so scan findings become repo-ready fixes.View product WooCommerce PluginPublish UCP discovery and agent-ready commerce signals from WooCommerce without rebuilding checkout.View product Shopify PluginAdd UCP discovery, storefront metadata checks, and controlled cart-to-checkout flows for shopping agents.View product AgentReady CIScan commits and PRs, publish reports, and choose which agent-readiness failures should block merges.View product

CanAgentUse tools

UCP Suite

Validate Universal Commerce Protocol discovery, then test product search, carts, checkout links, and merchant handoff flows.

UCP ValidatorUCP Playground

MCP Playground

Connect to remote MCP servers, inspect tools and resources, test prompts, auth, headers, notifications, and JSON-RPC responses.

MCP Playground

A2A Playground

Inspect Agent Cards, validate advertised endpoints, and prepare safe requests for agent-to-agent workflows.

A2A Playground

Agent Website Viewer

Enter a public URL and see the roles, names, landmarks, controls, and blockers that shape how AI agents understand the page.

Agent Website Viewer
New Scan
https://www.copy.ai/
SCANNED
Jul 6, 2026, 9:20 AM
VISIBILITY
Public
SUITE2026.06.10
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51/100

OVERALL SCORE

Level 3, Bot-Aware

Moderate readiness for AI agents
AIDiscoverability41%Agent Easeof Use49%Security& Trust68%GEO, AIO, AEO63%SEO92%Performance83%Accessibility31%
  • AI Discoverability 41 out of 100
  • Agent Ease of Use 49 out of 100
  • Security & Trust 68 out of 100
  • GEO, AIO and AEO 63 out of 100
  • SEO 92 out of 100
  • Performance 83 out of 100
  • Accessibility 31 out of 100

CAPTURED SCREENSHOT

Captured website desktop screenshot

What AI sees of your website

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Open Agent View

Next step

Turn this report into a fix workflow

2 failed checks are ready to move into MCP or CLI remediation. Generate a repair prompt, connect the scanner to your coding agent, or open the integration docs before your next rescan.

Fix with MCP / CLI
Detailed report scores grouped by capability area
MetricScoreStatusPassedFailedWarningEvidence
AI Discoverability
41
Priority fix1410View details
Discoverability
47
Priority fix600
Content Readiness
30
Priority fix700
Bot Access Control
45
Priority fix110View details
Agent Ease of Use
49
Priority fix342View details
Skill Discovery
48
Priority fix232View details
Google Agentic Browsing
48
Priority fix110View details
GEO, AIO and AEO
63
Needs work1000
GEO Readiness
Not Applicable
Not Applicable300
AIO Readiness
Not Applicable
Not Applicable400
AEO Readiness
Not Applicable
Not Applicable300
SEO
92
Strong900
SEO
92
Strong900
Security & Trust
68
Needs work1700
Security & Trust
68
Needs work1700
Performance
83
Mostly ready1200
Performance
83
Mostly ready1200

Prioritized recommendations

Issues ranked by score impact

3 items need attention

Agent Ease of UseSkill DiscoveryEmerging recommendation

agents.json

agents.json failed at "Validate Wildcard schema shape".

75 Fail

Needs attention

agents.json

Failed check
01

Issue

agents.json response is not valid JSON.

Details

02

Why it matters

Wildcard agents.json gives agents workflow-level context beyond plain OpenAPI, including flows, links, examples, and API action structure. It is an emerging OpenAPI-adjacent proposal, so scanners should validate the contract shape without treating it as an A2A or IETF standard.

Check name

agents.json

Score

25/100

Status

fail

Category

Skill Discovery

Maturity

Emerging recommendation

Goal

Publish a Wildcard-style agents.json file so agents can discover OpenAPI-backed workflows, links, examples, and authentication requirements.

Result

agents.json failed at "Validate Wildcard schema shape".

Validation steps

  1. Discover agents.json

    agents.json was found only at the fallback /agents.json path.

    agents.json is missing or only available at a fallback path

  2. Validate Wildcard schema shape

    agents.json response is not valid JSON.

    agents.json schema shape is invalid or incomplete

  3. Validate API actions

    Wildcard agents.json must include valid OpenAPI-derived action or operation definitions.

    agents.json action definitions are invalid or missing

  4. Validate flows and links

    No executable flows were found.

    agents.json flows or links are invalid

  5. Review examples and LLM usability

    Examples or descriptions are too thin for reliable agent argument generation.

    agents.json examples or descriptions need improvement
Evidence log5 steps · 23 lines
Discover agents.json [warning]! agents.json was found only at the fallback /agents.json path.INFODiscover agents.jsonINFOTry agents.json discovery paths in priority order paths=["/.well-known/agents.json","/agents.json"]WARNagents.json candidate path did not return a usable contract path="/.well-known/agents.json" statusCode=404 contentType="text/html; charset=utf-8"PASSFound an agents.json candidate path="/agents.json" statusCode=200 contentType="application/json" bytes=445987WARNSelected fallback agents.json location path="/agents.json" requestedUrl="https://www.copy.ai/agents.json"WARNagents.json was found only at the fallback /agents.json path.Validate Wildcard schema shape [fail]! agents.json response is not valid JSON.INFOValidate Wildcard schema shapeINFOParse agents.json and classify contract shape shape="unknown"FAILCompare contract shape actual="unknown" expected="wildcard"FAILCompare missing required schema fields actual="none" expected="none"FAILCompare Content-Type with JSON expectation actual=true expected=trueFAILagents.json response is not valid JSON.Validate API actions [fail]! Wildcard agents.json must include valid OpenAPI-derived action or operation definitions.INFOValidate API actionsFAILCompare API action count actual=0 expected="> 0"FAILCompare invalid action definitions actual=0 expected=0FAILWildcard agents.json must include valid OpenAPI-derived action or operation definitions.Validate flows and links [fail]! No executable flows were found.INFOValidate flows and linksFAILCompare workflow flow count actual=0 expected="> 0"FAILCompare operation link issues actual=0 expected=0FAILNo executable flows were found.Review examples and LLM usability [warning]! Examples or descriptions are too thin for reliable agent argument generation.INFOReview examples and LLM usabilityWARNCompare usable example count actual=0 expected="> 0 when actions are present"WARNExamples or descriptions are too thin for reliable agent argument generation.

AI DiscoverabilityBot Access ControlEstablished

AI bot rules in robots.txt

AI bot rules in robots.txt failed at "Classify AI crawler rules".

69 Fail

Needs attention

AI bot rules in robots.txt

Failed check
01

Issue

No explicit User-agent rules were found for major AI crawler tokens.

Details

02

Why it matters

AI crawler product tokens have different meanings. Explicit robots.txt groups make training, search, and retrieval access policy auditable for compliant crawler operators.

Check name

AI bot rules in robots.txt

Score

31/100

Status

fail

Category

Bot Access Control

Maturity

Established

Goal

Declare deliberate robots.txt rules for major AI training, AI search, user-triggered, and dataset crawlers.

Result

AI bot rules in robots.txt failed at "Classify AI crawler rules".

Validation steps

  1. Classify AI crawler rules

    No explicit User-agent rules were found for major AI crawler tokens.

    robots.txt lacks explicit AI crawler rules
Evidence log1 step · 6 lines
Classify AI crawler rules [fail]! No explicit User-agent rules were found for major AI crawler tokens.INFOClassify AI crawler rulesINFOParsing User-agent groups and Allow/Disallow records for known AI crawler tokens evaluatedPath="/"INFOEvaluating exact User-agent matches before wildcard fallback exactAiPolicyCount=0 totalCrawlerTokens=18FAILNo explicit AI crawler User-agent groups were found examplesExpected=["GPTBot","OAI-SearchBot","ClaudeBot","Google-Extended","CCBot"]FAILCompare explicit AI crawler coverage actual=0 expected="> 0 explicit non-search AI crawler policies" missingTokens=["GPTBot","OAI-SearchBot","ChatGPT-User","ClaudeBot","Claude-SearchBot","Claude-User","Google-Extended","Applebot-Extended","Amazonbot","Amzn-SearchBot","Amzn-User","PerplexityBot"]INFOResolved effective root-path policy for crawler tokens blocked=0 allowed=21 unspecified=0

Agent Ease of UseGoogle Agentic BrowsingBrowser audit

Accessibility tree is not well-formed

100 Fail

Check name

Accessibility tree is not well-formed

Score

0/100

Status

fail

Device

desktop

Category

Google Agentic Browsing

Fix guidance

A well-formed [accessibility tree](http://goo.gle/lighthouse-agentic-a11y) helps AI agents to navigate and interact with the page.

Evidence
{
  "description": "A well-formed [accessibility tree](http://goo.gle/lighthouse-agentic-a11y) helps AI agents to navigate and interact with the page."
}

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Fix with MCP / CLI

Score history

Public scan score over time

Public reports for this website origin. Select any point or report link to open that canonical report.

2 reports
Public score history report links
Scan dateScoreReadinessReport
53/100Level 3, Bot-AwareView report
51/100Level 3, Bot-AwareCurrent report