APIs are mechanisms that enable two software components to communicate with each other using a set of definitions and protocols.
Connecting AI models to data sources is tough—custom integrations are time-consuming. Model Context Protocol (MCP) simplifies this by standardizing how models interact with tools. This guide explores how MCP works and why it could be a game-changer for developers.
AI APIs promise powerful capabilities, but their documentation rarely tells the full story. Security gaps, performance issues, and design flaws can surface in production, causing costly setbacks. We put top AI APIs to the test with API Insights to uncover real-world insights—here’s what we found.
Testing and developing APIs is becoming increasingly complex, but AI-powered tools are changing the game. From automated test generation to intelligent debugging, these solutions enhance efficiency, security, and performance. In this guide, we’ll explore the top AI tools to streamline your workflow.
AI is reshaping API workflows—automating documentation, accelerating debugging, and strengthening security. With APIs growing more complex, manual processes can’t keep up. In this article, we’ll explore 8 ways AI optimizes API development, helping teams build faster and smarter.
On February 26, 2025, Slack faced a major outage, disrupting thousands of users due to API failures from database shard issues. This highlights the need for API intelligence to catch issues early and prevent downtime. Here’s what went wrong—and how to avoid similar failures.
APIs power modern apps, but outdated docs, debugging errors, and security risks slow teams down. AI transforms API management by automating tasks, improving accuracy, and enhancing security. Here are seven common API challenges and how AI helps solve them.
Building an API is easy—getting developers to adopt it isn’t. Alfred AI and Postbot help with integration, testing, and debugging. Which one is right for you? Let’s compare their features and use cases.
AI agents are transforming industries, automating tasks, and making smarter decisions. But without real-time data, they fall short. APIs provide the missing link, powering AI with live information. This article explores how APIs enhance AI capabilities, the challenges they pose, and what’s next.
Great API documentation drives adoption, reduces integration time, and improves developer experience. This guide explores eight standout examples, highlighting what makes them effective and how you can apply their best practices.
