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Guides, concepts, and best practices for building APIs that AI agents can discover, understand, and execute.
Comparisons
Reference guides
What is agent.json?
The standard for AI agent API discovery — format, examples, and implementation.
What is MCP?
Model Context Protocol explained — architecture, configs, and how it works.
What is llms.txt?
Making your site readable by LLMs — format, best practices, and examples.
All articles
Best API Documentation for AI Agents
Complete guide to API documentation platforms for AI agents. Compare Elba, Swagger, Mintlify, ReadMe, and Postman.
How to Make Your API Usable by AI Agents
What it means for an API to be agent-ready, why traditional docs fail, and how to fix it.
What is agent.json and Why It Matters for AI Agents
agent.json is a machine-readable file that describes an API for AI agents. Learn how it works and why it matters.
MCP Explained: Model Context Protocol for API Integration
What MCP is, how it works, and why it matters for AI agent tool use and API integration.
What is llms.txt and How It Helps AI Understand Your API
llms.txt gives LLMs a simplified overview of your API. Learn best practices for writing one.
API Discovery for AI Agents: How It Works
How AI agents find and evaluate APIs without manual input, and why discovery is the next distribution channel.
Why AI Agents Hallucinate API Calls and How to Fix It
API hallucination happens when agents invent endpoints or misuse parameters. Learn the causes and solutions.
API SEO: How to Optimize Your API for AI Agent Discovery
API SEO is the process of making your API findable by AI agents through structured metadata and indexing.
Best Practices for Designing APIs for AI Agents
Design principles, common mistakes, and how to think in actions instead of endpoints.
Structured Actions vs REST Endpoints: What AI Agents Need
Why agents think in actions and outcomes, not resources and endpoints. The shift to action-based APIs.
The Future of APIs: From Human Developers to AI Agents
The primary users of APIs are changing. New documentation standards, discovery mechanisms, and execution layers are emerging.
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