Agent Income Lab

AI agents are changing how people discover information, compare products, and interact with digital services. Learn how to prepare your website for ChatGPT Search, Claude, Google AI features, and the emerging agent-driven internet.

Published: October 24, 2026
Category: AI Agent Economy & Monetization
Reading time: Approximately 15–18 minutes
Difficulty: Beginner to Intermediate

Introduction: What If Your Next Website Visitor Is an AI Agent?

Imagine you operate a website offering specialized business software, technical documentation, or professional services.

Traditionally, potential customers discover your website through Google Search, advertising, referrals, or social media.

They open your pages, read the content, evaluate your products, and contact your business.

But internet discovery is changing.

Today, users can ask AI assistants to research companies, compare software, recommend services, and gather information from multiple websites.

Instead of manually browsing ten different websites, a customer might ask:

“Find three companies offering AI automation consulting for small businesses in the Netherlands.”

An AI assistant may search for suitable providers, examine available information, and present recommendations.

In more advanced workflows, autonomous AI agents can interact with external software tools, retrieve structured data, and execute authorized operations.

For website owners, this raises an important question:

How do you make your website understandable, accessible, and useful to AI agents?

The answer involves more than traditional search engine optimization.

It includes technical crawling policies, structured content, machine-readable information, APIs, and potentially Model Context Protocol (MCP) integrations.

But there is also a danger of overcomplicating the process.

Many websites do not need a custom AI-agent framework to become more discoverable.

A technically accessible website with useful, trustworthy, well-organized content remains an excellent starting point.

In this guide, we will examine 15 practical steps website owners can take to improve their readiness for AI-powered discovery and agent interaction.

We will also explain the difference between making content discoverable and making software capabilities usable by AI agents.

1. Understand the Three Levels of AI Agent Discoverability

The first step is understanding what discoverability actually means.

Not every AI system interacts with websites in the same way.

Level 1: AI search discoverability

An AI search system discovers, retrieves, and evaluates website content.

For example, a user asks ChatGPT to recommend tools for automating sales processes.

The search system may retrieve relevant webpages and use them as sources when producing an answer.

Your objective is to make the site’s public information accessible, understandable, and relevant.

Level 2: User-directed agent access

An AI assistant may visit a website because a user explicitly asks it to retrieve information.

For example:

“Read the installation instructions on this website and summarize the requirements.”

This differs from scheduled crawling or search indexing.

A user-directed agent may retrieve individual pages as part of an interactive workflow.

Level 3: Tool and API discovery

At this level, the agent uses a website’s software capabilities rather than merely reading its content.

For example:

“Generate a company-research report using this provider’s API.”

The agent needs an available tool interface, suitable permissions, and clear instructions.

These interfaces may be REST APIs, OpenAPI-based integrations, or MCP tools.

Why the distinction matters

A WordPress publisher primarily concerned with being cited in AI search results should begin with content and technical SEO.

A SaaS developer who wants AI agents to execute paid research requests needs API documentation, authentication, and integration support.

Some businesses need both.

AI discoverability is not one feature. It is a combination of content discovery, authorized access, and machine-consumable functionality.

2. Allow Relevant AI Search Crawlers

Before optimizing content, make sure authorized crawlers can access it.

Many website owners use a robots.txt file to communicate crawling preferences.

This file is typically located at:

https://example.com/robots.txt

It tells compliant crawlers which parts of a website they may request.

Different AI companies operate different crawlers.

For example, OpenAI documents separate crawler identities for AI search, model training, and certain user-directed requests.

Important OpenAI crawlers

These identities should not be treated as interchangeable.

According to OpenAI’s documentation, website owners can allow OAI-SearchBot while blocking GPTBot.

That distinction lets a publisher express different preferences for search visibility and training-related crawling.

Also note that ChatGPT-User is not an automatic search crawler, and robots.txt rules may not apply to every user-directed request.

Example robots.txt configuration

Suppose you want to allow ChatGPT Search discovery but opt out of GPTBot training-related crawling.

A simplified configuration would be:

User-agent: OAI-SearchBot
Allow: /
User-agent: GPTBot
Disallow: /
User-agent: *
Allow: /
Sitemap: https://example.com/sitemap_index.xml

Replace the example sitemap address with your actual XML sitemap.

This configuration does not guarantee that ChatGPT will cite or recommend your website.

It simply communicates the intended crawler access policy.

Also check your CDN, web application firewall, hosting provider, and server logs.

A crawler can be allowed in robots.txt yet still be blocked by another security system.

Official reference: https://developers.openai.com/api/docs/bots

3. Understand Claude’s AI Crawlers

Anthropic also documents different crawler identities.

These include:

ClaudeBot: Associated with collecting web content that may contribute to model development.

Claude-SearchBot: Supports web search discovery and search-result quality.

Claude-User: Retrieves website content in response to certain user requests.

These functions are different.

If your objective is discoverability in Claude search, indiscriminately blocking every Anthropic crawler may be counterproductive.

For example:

User-agent: Claude-SearchBot
Allow: /
User-agent: Claude-User
Allow: /
User-agent: ClaudeBot
Disallow: /

This example expresses a preference for allowing search and user-directed access while restricting training-related crawling.

It does not guarantee visibility in Claude answers.

The exact policy should reflect your business objectives and the current documentation.

Official reference: https://support.anthropic.com/en/articles/8896518-does-anthropic-crawl-data-from-the-web-and-how-can-site-owners-block-the-crawler

4. Do Not Forget Google Search

Google remains a major discovery channel.

Its AI Overviews and AI Mode are integrated into Google Search.

Google’s official guidance emphasizes that the fundamental technical and content requirements for Search continue to apply to its AI features.

Website owners generally do not need to create a separate AI-only version of their pages to appear in Google’s AI search experiences.

Focus on established practices such as:

• Allowing relevant Googlebot crawling.
• Making important pages indexable.
• Providing useful, original content.
• Using descriptive page titles.
• Creating logical internal links.
• Maintaining a sitemap.
• Improving the mobile experience.
• Keeping information accurate and current.

Google also documents controls such as noindex, nosnippet, and max-snippet for managing search visibility and previews.

These controls have specific consequences.

Do not introduce restrictive directives without understanding their impact.

Official reference: https://developers.google.com/search/docs/appearance/ai-features

5. Publish Clear, Structured Content

Technical accessibility is only part of the problem.

The content must also communicate useful information.

AI systems frequently need to identify definitions, product capabilities, comparisons, procedures, and factual details.

A poorly organized page may make those tasks harder.

Consider two ways to describe a service.

Weak description

“We deliver next-generation solutions to transform your business through innovative intelligence.”

This sounds impressive but provides little specific information.

Better description

“Our company provides AI automation consulting for small businesses, including workflow design, CRM integrations, document processing, and custom AI agent development.”

The second description identifies the services more clearly.

It helps both human readers and automated systems understand the business.

Recommended content structure

Use:

• One descriptive H1 heading.
• Logical H2 and H3 sections.
• Clear definitions.
• Practical examples.
• Relevant comparisons.
• Technical requirements where appropriate.
• Frequently asked questions when genuinely useful.
• Source references for important claims.
• Visible author and update information when relevant.

Avoid inserting keywords unnaturally.

The objective is to communicate meaning, not to repeat the phrase “AI agents” as frequently as possible.

6. Answer Specific Questions Directly

AI-assisted search often begins with natural-language questions.

For example:

“What is an MCP server?”

“Can AI agents pay for API requests?”

“How do I monetize a Python research API?”

A useful educational article should answer its main question clearly near the beginning.

Consider this format:

What is an MCP server?

An MCP server exposes tools, resources, and prompts to compatible AI applications through the Model Context Protocol.

Follow that definition with practical examples, limitations, and implementation details.

This improves readability and gives retrieval systems a clearly expressed explanation.

However, no content format guarantees inclusion in AI-generated answers.

Quality, relevance, accessibility, competing sources, and platform-specific retrieval behavior all matter.

7. Implement Appropriate Structured Data

Structured data makes selected information about a webpage explicit.

Schema.org provides vocabularies for representing entities such as organizations, articles, products, software applications, and frequently asked questions.

For example, a website can describe its organization with JSON-LD.

Example Organization schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Example Software Company",
  "url": "https://example.com",
  "description": "Developer tools and AI automation services."
}
</script>

For an article, appropriate structured data might include:

• Headline.
• Author.
• Publication date.
• Modification date.
• Publisher.
• Main image.

Important limitations

Structured data should accurately represent information visible on the page.

Do not invent author credentials, customer reviews, ratings, or product claims.

Schema.org markup is also not a universal agent-discovery system.

It can help search engines interpret certain page attributes, but it does not automatically make an API callable or an MCP tool available.

Use structured data as part of a broader technical SEO strategy.

Official references:

8. Publish Accurate Product and Service Information

If you sell software, APIs, consulting, or digital products, make the commercial information explicit.

An AI research agent may want to understand:

• What does the product do?
• Who is it for?
• What are its main capabilities?
• What does it cost?
• Which integrations are supported?
• Are there geographic restrictions?
• Is there a free plan?
• How can customers obtain access?

Avoid hiding essential information behind vague marketing language.

For example, a useful API product page could include:

Product: Company Research API

Purpose: Returns structured company intelligence for authorized clients.

Inputs: Company name, country, and report type.

Outputs: JSON reports containing research findings and evidence.

Authentication: API key.

Pricing: Published subscription or usage-based plan.

Availability: Countries and customer types supported.

Documentation: Link to API reference.

This does not mean that AI agents will automatically purchase the product.

It means the information required to evaluate the offering is easier to find.

9. Provide an OpenAPI Specification

For developers who want AI agents to interact with software, OpenAPI is particularly useful.

OpenAPI describes HTTP APIs in a machine-readable format.

It can define:

• Available endpoints.
• HTTP methods.
• Request parameters.
• Request bodies.
• Response schemas.
• Authentication requirements.
• Error responses.

For example, FastAPI automatically generates an OpenAPI document.

A default FastAPI application exposes:

https://api.example.com/openapi.json

And interactive documentation at:

Example API endpoint

from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI(
    title="Company Research API",
    version="1.0.0"
)
class ResearchRequest(BaseModel):
    company: str
    country: str
@app.post("/api/research")
def research(request: ResearchRequest):
    return {
        "company": request.company,
        "country": request.country,
        "status": "demo",
        "message": "Example response only"
    }

The endpoint provides a basic machine-readable interface.

A production service would also require proper authentication, authorization, usage accounting, and reliable research logic.

Does OpenAPI guarantee AI-agent discovery?

No.

An OpenAPI specification makes integration easier, but the agent’s environment still needs an approved way to discover or connect to the service.

For example, a developer might explicitly register the API as a tool available to an agent.

The specification does not automatically cause every public AI assistant to discover and invoke the endpoint.

10. Consider Creating an MCP Server

The Model Context Protocol provides another way for compatible AI applications to interact with external capabilities.

An MCP server can expose tools such as:

• Generate a company report.
• Search a product database.
• Validate a technical configuration.
• Calculate a service quotation.
• Retrieve a licensed dataset.

This is particularly relevant if your business sells software capabilities rather than only content.

Example: Research MCP server

Suppose you have a company-research API.

An MCP interface could expose:

generate_company_snapshot

The tool description specifies its purpose and parameters.

An authorized AI client can invoke the tool and receive a structured result.

The underlying research engine can remain the same.

Publishing MCP tools

The Model Context Protocol ecosystem has an official MCP Registry for discovering published servers.

Developers who operate an appropriate MCP server can investigate the registry’s publishing procedures, namespace verification, and metadata requirements.

However, registry publication is not the same as universal availability in every AI application.

Client platforms have their own connection and approval requirements.

Official registry:

Documentation:

11. Make Your Website Technically Accessible

Even excellent content may be difficult to retrieve if the website has technical problems.

Review these areas.

HTTP status codes

Public content should normally return HTTP 200.

Missing pages should return appropriate error codes.

Avoid unnecessary redirects or broken canonical URLs.

Server-side content

Important information should be present in accessible HTML.

If a page requires complicated client-side rendering before its content appears, some automated clients may not retrieve it successfully.

Modern search systems can render JavaScript in various circumstances, but relying unnecessarily on complex rendering introduces additional failure points.

Page speed

Slow pages waste crawler resources and frustrate human visitors.

Optimize images, caching, scripts, and server response times.

Mobile usability

Ensure important content works on smaller screens.

Canonical URLs

Use appropriate canonical links for pages with duplicate or substantially similar URLs.

XML sitemap

Publish a current sitemap containing the canonical URLs you want search engines to discover.

For WordPress, the sitemap may be provided by WordPress itself or an SEO plugin.

HTTPS

Use valid TLS certificates and avoid mixed-content problems.

These are conventional web engineering practices.

They remain valuable in the AI search environment.

12. Be Careful with Anti-Bot Security Rules

Many websites use Cloudflare, another CDN, or hosting security tools to manage automated traffic.

These controls can be useful for preventing abuse.

However, overly aggressive security settings may block legitimate search crawlers or authorized user-directed agents.

For example, a bot-protection rule might unexpectedly challenge requests from an otherwise permitted AI search crawler.

A crawler cannot necessarily complete an interactive CAPTCHA.

As a result, it may be unable to retrieve the page.

What to review

Check whether your security infrastructure is:

• Blocking known search crawlers.
• Requiring JavaScript challenges for public content.
• Returning HTTP 403 unexpectedly.
• Applying restrictive geographic rules.
• Rate-limiting compliant crawlers excessively.
• Blocking published crawler IP ranges.

Do not trust a user-agent header alone as proof of identity.

User-agent strings can be forged.

Where available, use the crawler operator’s published IP information or your security provider’s verified-bot identification features.

The objective is selective access control, not removing all security protections.

13. Do You Need an llms.txt File?

You may encounter recommendations to publish an llms.txt file.

The proposed convention uses a text file to describe a website and link to important machine-readable resources.

For example:

# Example Developer Website
Developer tutorials and API documentation.
## Documentation
- https://example.com/docs/
- https://example.com/api/
- https://example.com/tutorials/

This can be useful as an additional documentation index.

However, it is important to distinguish the proposal from an established universal standard.

There is no demonstrated requirement that a website must publish llms.txt to appear in ChatGPT Search, Claude search, or Google AI features.

Nor is there reliable evidence that publishing the file alone produces a ranking advantage.

For most website owners, correct crawling permissions, indexable content, useful documentation, and established SEO practices should receive priority.

If you choose to experiment with llms.txt, treat it as an optional enhancement rather than a substitute for your normal website structure.

14. Can You Charge AI Agents and Still Remain Discoverable?

Yes.

A useful strategy is to separate public discovery from paid consumption.

Imagine a website selling specialized market-research reports.

Its public pages might include:

• Educational articles.
• Service descriptions.
• API documentation.
• Pricing information.
• Sample reports.

Those pages can remain freely accessible.

The actual research API can require payment.

For example:

Public endpoint:

GET /api/products

Returns general information about available services.

Paid endpoint:

POST /api/research/company

Requires authorization and a commercial entitlement.

This approach allows potential customers and authorized discovery systems to understand the product before purchasing it.

Where x402 fits

A compatible paid API can communicate payment requirements through the x402 protocol.

However, machine-payment support is not necessary for basic website discoverability.

It is an additional commercial capability.

For many smaller businesses, traditional subscriptions or prepaid API credits may remain easier to manage.

15. How to Measure AI Agent Discoverability

Measurement is one of the more difficult parts of this topic.

Traditional SEO tools focus on search impressions, rankings, organic visits, and conversions.

AI-assisted discovery introduces additional questions.

For example:

• Can ChatGPT Search retrieve your content?
• Does an AI answer cite your website?
• Does Claude reference your documentation?
• Are AI users reaching your website through referrals?
• Are approved agents successfully accessing your APIs?
• Do those visits lead to paid customers?

Different tools measure different parts of the process.

Useful measurement categories

Crawler accessibility

Inspect whether relevant bots can request important pages.

Search indexing

Use tools such as Google Search Console to monitor search indexing and visibility.

AI citations

Test a defined portfolio of relevant prompts and record citations to your website.

Brand mentions

Record whether the website, product, or business is mentioned in responses.

Referral traffic

Monitor identifiable visits from AI platforms where attribution data is available.

Agent API usage

Track authenticated tool calls, successful requests, response times, and errors.

Do not confuse activity with commercial value

A crawler retrieving 10,000 pages does not necessarily create 10,000 commercial opportunities.

Likewise, one AI citation does not automatically produce a visitor or sale.

A useful measurement framework distinguishes discovery, recommendation, engagement, and conversion.

Also remember that AI-generated answers can vary between runs.

Repeated measurements and consistent test conditions are necessary before interpreting changes as meaningful trends.

16. A Practical AI Discoverability Checklist

Use this checklist when evaluating your own website.

Website crawling

• Public pages are accessible without authentication.
• Important content returns HTTP 200.
• robots.txt reflects the intended AI crawler policy.
• Search crawlers are not accidentally blocked by the CDN.
• XML sitemap is current.
• Canonical URLs are configured correctly.

Content and structured information

• Every important page has a descriptive title.
• Headings follow a logical hierarchy.
• Core questions receive direct answers.
• Content includes relevant examples.
• Organization and article details are accurate.
• Appropriate structured data is implemented.
• Important claims are supported by trustworthy sources.

Product and service discovery

• Product capabilities are clearly explained.
• Pricing or the quotation process is understandable.
• Supported integrations are documented.
• Geographic availability is specified where relevant.
• Contact and support information is easy to locate.

API and agent integration

• APIs have machine-readable documentation.
• Request and response schemas are explicit.
• Authentication requirements are documented.
• Errors use predictable HTTP responses.
• Rate limits and usage rules are communicated.
• MCP tools are available where commercially useful.
• Paid operations enforce authorization independently of the AI model.

Measurement

• Search indexing is monitored.
• Crawler errors are reviewed.
• Important AI search queries are tested periodically.
• AI citations are recorded with supporting evidence.
• Agent API requests are tracked.
• Commercial conversions are measured separately from crawler activity.

17. WordPress-Specific Recommendations

For publishers using WordPress, many improvements can be made without writing custom software.

Use descriptive permalinks

Prefer:

/how-to-build-ai-agents/

rather than query-based or unexplained numeric URLs.

Maintain an SEO plugin

A reputable SEO plugin can help manage titles, descriptions, canonical tags, and XML sitemaps.

Verify the generated output rather than assuming every configuration is correct.

Add appropriate article schema

Provide accurate author, headline, publication, and modification information.

Create topical content clusters

Group related articles under coherent categories.

For example, a developer website might publish a series covering:

• AI agent architecture.
• MCP tools.
• Agent payments.
• Paid APIs.
• Agent-native SaaS.
• Security and observability.

Link related articles together.

Avoid duplicating introductory text excessively

Each article should address a distinct question or provide unique practical value.

Publishing many pages with nearly identical information can weaken the usefulness of the site.

Keep technical tutorials current

Software APIs, SDKs, and specifications change.

Review tutorials when major releases affect installation instructions, code, or behavior.

Display updated dates when substantive changes occur.

18. A 30-Day Implementation Plan

For a small website, I recommend a manageable four-week plan.

Week 1: Technical access audit

Inspect robots.txt, sitemap configuration, HTTP responses, indexing status, and security rules.

Identify important public pages that automated clients cannot retrieve.

Week 2: Content improvements

Choose ten commercially important pages.

Improve titles, opening summaries, headings, product descriptions, and source references.

Ensure each page addresses a distinct audience question.

Week 3: Structured interfaces

If you sell software capabilities, improve API documentation.

Publish or update the OpenAPI specification.

If relevant, create a small MCP proof of concept.

Do not introduce a paid agent interface unless there is a genuine product use case.

Week 4: Measurement

Create a list of 20–30 prompts relevant to your business.

Test them under documented conditions.

Record whether your brand or pages are mentioned or cited.

Review crawler access and server logs.

Use the results as a baseline rather than assuming that a single measurement reveals a permanent ranking.

19. Example: Preparing an AI Development Website for Agent Discovery

Consider a website focused on AI development tutorials and downloadable software resources.

It publishes:

• Python tutorials.
• MCP server guides.
• AI-agent business ideas.
• API monetization examples.
• Free developer starter kits.

A practical discoverability strategy would involve several layers.

Public educational content

Keep tutorials accessible and clearly structured.

Explain technical concepts accurately.

Provide complete code examples where useful.

Downloadable developer resources

Create dedicated landing pages describing what each starter kit includes.

Publish version information, requirements, licensing terms, and installation instructions.

Technical documentation

For any hosted API, provide an OpenAPI specification and clear authentication documentation.

Optional MCP integration

If the business offers a hosted research service, consider exposing useful capabilities through MCP.

Commercial access

Separate free documentation from premium operations.

Use secure authentication and a supported billing method.

Measurement

Monitor relevant search queries, citations, referral traffic, downloads, and paid conversions.

This structure allows the website to serve human visitors and authorized AI applications without abandoning conventional SEO.

20. Frequently Asked Questions

How do I make my website discoverable to AI agents?

Start with accessible HTML, correct crawler permissions, useful content, clear structure, and established technical SEO. Add documented APIs or MCP interfaces when agents need to execute operations.

How do I get my website into ChatGPT Search?

OpenAI recommends allowing OAI-SearchBot and its published IP ranges. Inclusion and citation are not guaranteed.

Can I block GPTBot and still appear in ChatGPT Search?

Yes. OpenAI documents independent crawling controls for GPTBot and OAI-SearchBot. These serve different purposes.

Does Claude use a separate search crawler?

Yes. Anthropic documents Claude-SearchBot separately from ClaudeBot and Claude-User.

Do I need an llms.txt file?

No. It is optional and is not a documented universal requirement for major AI search systems.

Does structured data guarantee AI recommendations?

No. Structured data can help clarify information, but it does not guarantee ranking, citation, or recommendation.

Is OpenAPI important for AI agents?

OpenAPI is valuable when you want software applications to integrate with your HTTP API. It describes endpoints, inputs, outputs, and authentication requirements.

Should every website have an MCP server?

No. MCP is useful when a business provides tools or data that compatible AI applications need to invoke.

Can AI agents access WordPress websites?

Yes, subject to technical accessibility, the agent’s capabilities, and applicable access controls. A public WordPress site does not automatically require an MCP server.

Will allowing AI crawlers improve SEO?

Allowing relevant crawlers enables access, but access alone does not guarantee improved visibility or rankings.

Should I charge AI agents for accessing my content?

That depends on the business model. Public educational content may provide greater value through discovery, while specialized APIs or proprietary datasets may justify paid access.

Can AI agents purchase services from my website?

Potentially, if you provide supported commerce or API integrations and the agent has appropriate authorization. Not all agents support autonomous payments.

How can I measure AI visibility?

Use a consistent set of prompts, record mentions and citations, review referrals, and measure commercial outcomes separately from crawler requests.

Conclusion: Build a Website That Both Humans and Agents Can Understand

The internet is evolving toward a world where more information retrieval and software interaction happens through AI assistants and autonomous agents.

For website owners, this creates both challenges and opportunities.

Traditional SEO remains important.

Websites still need accessible pages, useful content, clear structure, and reliable technical infrastructure.

But businesses that offer digital products or software capabilities may also benefit from machine-readable interfaces.

An OpenAPI specification can make integration easier.

An MCP server can expose useful tools to compatible AI applications.

A secure commercial layer can allow authorized customers to purchase premium services.

The important principle is to avoid confusing these different capabilities.

Being discoverable in AI search is not the same as being callable as an AI-agent tool—and neither automatically guarantees revenue.

Start by making your website easy to discover and understand.

Then determine whether your audience would benefit from tools or APIs that agents can actually use.

Finally, validate whether those capabilities create commercial value.

The next generation of successful websites may combine excellent human-readable content with dependable machine-consumable services.

For independent developers and entrepreneurs, learning to support both is a worthwhile investment.

Continue Reading at Agent Income Lab

This article is part of the AI Agent Economy & Monetization series.

Previous articles:

• The War on AI Agents: Why Websites Are Starting to Charge AI Bots.
• What Is the AI Agent Economy? A Beginner’s Guide for 2026.
• How AI Agents Will Change the Way Websites Make Money.
• What Is HTTP 402? The Payment Protocol Behind AI Agent Commerce.
• What Is x402? How AI Agents Can Pay for APIs and Data.
• Cloudflare Monetization Gateway: How to Charge AI Agents.
• How to Build an API That AI Agents Can Pay to Use.
• How to Monetize an MCP Server in 2026.
• 10 AI Agent Economy Business Ideas for 2026.
• Google Agent Payments Protocol (AP2): A Developer’s Guide.
• How to Build a Paid Research API for AI Agents.
• AI Agent Payments vs Traditional API Subscriptions.

Free resource:

Free Paid AI Research API Starter Kit — Python & FastAPI Source Code.

Next articles:

• Article 014 — How to Price APIs, Datasets, and MCP Tools for AI Agents.
• Article 015 — Build Your First Agent-Native Micro-SaaS: Complete Tutorial.

Visit Agent Income Lab for practical developer tutorials, downloadable starter kits, and AI software monetization strategies.

Official Sources and References

1. OpenAI — Overview of OpenAI Crawlers
2. Anthropic — Web Crawlers and Website Owner Controls
3. Google Search Central — AI Features and Your Website
4. Google Search Central — Structured Data Introduction
5. Schema.org — Structured Data Vocabulary
6. FastAPI — Official Documentation
7. OpenAPI Initiative — Specification
8. Model Context Protocol — Official Documentation
9. Official MCP Registry
10. MCP Registry — Publishing and API Documentation

Editorial note: AI crawler identities, search behavior, and agent integration capabilities can change. This guide reflects publicly documented information as of October 24, 2026. No technical configuration guarantees inclusion, recommendation, or citations in AI-generated answers.