7 min read
GEO vs SEO: AI Visibility Strategy Guide
AI summaries changed search behavior: Pew found 8% click rates with summaries vs 15% without. Build SEO, GEO, AIO, and agent readiness as one measurable system.
Scanner for the agentic web
Is your website ready for AI agents?
Run an evidence-based AI SEO scan across crawler policy, structured data, performance, accessibility, API discovery, OAuth, MCP, WebMCP, agent skills, and commerce-readiness signals.
Scanner coverage
129 signals across 15 readiness areas for the AI agent age.
The scanner measures whether websites and web apps give AI systems the signals they need to discover public pages, trust crawler policy, understand content, call documented APIs, and complete approved workflows.
Agent reliability
66
Discovery, content, APIs, auth, MCP, commerce
Security & policy
9
Headers, crawler trust, training policy
GEO, AIO and AEO
22
AI citations, AI Overview, and answer-engine readiness
Performance & accessibility
32
Performance, accessibility, SEO, and best practices
Latest guides
Agent-readiness field notes
7 min read
OpenAPI to MCP: Complete Agent API Guide
Agents need more than crawlable pages. Build an action layer with OpenAPI, OAuth, MCP tools, safe confirmation, measurable workflows, and audit logs now.
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AI Crawler Access: Essential 2026 Playbook
OpenAI, Anthropic, and Perplexity split training, search, and user-fetch bots. Allow AI visibility without losing control of training access or edge security.
Developer Toolkit
Integrate the MCP Server. Automate CLI in CI/CD.
The readiness scanner operates as a standalone CLI tool, an MCP server, and a CI/CD regression gate. Connect it to Claude or Cursor for local repair workflows, run public or localhost scans from the terminal, and compare saved reports to block regressions before a preview build ships.
Integration Options
Engine Capabilities
Stateless & Fast
Zero-dependency, in-memory execution
Local-First Safe
Scans localhost & private network environments
Signals
Covers GEO, AIO, AEO, SEO, APIs, Auth, MCP, performance, and accessibility
Playbook-Linked
Every scan failure links directly to remediation steps
Step-by-step Setup
Connect to Claude Desktop or Cursor
Configure your AI editor to run the scanner locally. This allows the model to analyze directories, fetch playbooks, and draft config files automatically.
1. Copy Server ConfigurationShared configuration format
{
"mcpServers": {
"can-agent-use": {
"command": "npx",
"args": ["-y", "can-agent-use@latest"]
}
}
}2. Insert into config files:
Claude Desktop
Paste configuration into:
~/Library/Application Support/Claude/claude_desktop_config.jsonCursor IDE
Settings → Features → MCP → Add Server (or edit):
~/.cursor/mcp.json💡 Try asking your assistant:
›"Scan https://localhost:3000 and fix failing readiness rules"
›"Compare our production site with local build and show regressions"
›"Create a validated robots.txt file that permits AI bots"
Stateless & Fast
Local-First Safe
Signals
Playbook-Linked
Fully open source on GitLab under MIT License
Connect with us
Want help making your site agent-ready?
Send your site and goals. We can review readiness gaps, implementation options, and the right next step before or after you scan.
Meeting link unavailable
FAQs
Questions about AI SEO and agent-readiness scans
The scanner focuses on the public, machine-readable, technical, and content signals that AI search systems and agents need before they can cite, understand, or use a website reliably.
CanAgentUse checks AI SEO, crawler policy, structured data, semantic HTML, performance, accessibility, API catalog, OpenAPI, OAuth/OIDC discovery, protected resource metadata, MCP, WebMCP, A2A, agent skills, Web Bot Auth, AI training policy, and agent commerce signals such as x402, MPP, UCP, and ACP.
No. Robots.txt and llms.txt are only a small part of the scan. The report also evaluates content extraction, AI SEO, structured data, API discovery, authentication metadata, MCP and WebMCP surfaces, agent-facing skills, security headers, performance, accessibility, and commerce-readiness metadata.
Yes. It checks API catalog discovery, OpenAPI or Swagger documents, OAuth and OIDC discovery metadata, OAuth Protected Resource metadata, MCP server cards, mcp.json, WebMCP manifests, browser tool annotations, A2A agent cards, agent.json, agents.json, and agent skills indexes.
A report covers more than 120 readiness signals across AI discoverability, AI SEO, content readiness, bot access control, API, auth, MCP, skill discovery, security, training policy, agent commerce, performance, accessibility, SEO, and browser best-practice areas.
You get a scored report with captured screenshots, category scores, failed checks, warnings, evidence, issue details, remediation guidance, references, export options, and prompts that engineering teams can use to fix AI SEO and agent-readiness gaps.
SEO, growth, product, platform, developer relations, ecommerce, and engineering teams can use CanAgentUse to find gaps that stop AI systems from discovering, citing, understanding, authenticating with, or safely using a website or web application.