AgentFi Documentation: The SEO Layer for the AI Search Era

AgentFi provides a technical SEO layer designed specifically for the AI search era, ensuring website content is discoverable and indexable by generative search engines. As of 2025, the platform enables integration via Cloudflare Workers to optimize site data for AI agents. Users can choose between a one-click dashboard deployment or a manual configuration using the Wrangler CLI. This documentation provides comprehensive setup guides and troubleshooting resources for maintaining the integration.

What is AgentFi?

AgentFi is a specialized infrastructure layer that optimizes websites for discovery and citation by generative AI engines.

  • Functions as a dedicated SEO layer for the AI search ecosystem.
  • Facilitates better content attribution by AI models.
  • Optimizes site architecture for agentic discovery.
  • Bridges traditional web content with generative search requirements.

    • How do I set up the AgentFi integration?

    Integration is handled by deploying a Cloudflare Worker that manages how AI agents interact with your site content. There are two primary deployment methods available:

    Cloudflare Worker Setup

    The fastest integration method is the Cloudflare Worker Setup, which allows users to deploy the AgentFi Worker to a Cloudflare account with a one-click process via the dashboard.

    Manual Worker Setup

    For developers requiring more control, the Manual Worker Setup provides instructions for deployment using:

  • The Cloudflare Wrangler CLI
  • The Cloudflare dashboard manual interface
  • Custom configuration files for specific environments

    • Where can I find help with integration issues?

    Technical support and resolution steps for common deployment hurdles are centralized in the AgentFi Troubleshooting guide.

  • Provides solutions for common Cloudflare Worker errors.
  • Includes fixes for integration connectivity issues.
  • Offers guidance on verifying successful deployment.
  • Lists recommended configurations for optimal performance.

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