Savan is currently managing demand generation at Treblle. He is a formal engineer turned marketing guy who loves to solve dev marketing problems.
Traditional APIs like REST and GraphQL have powered integrations for years, but modern systems demand more flexibility. This article explores how MCP compares to traditional APIs—covering use cases, pros, cons, and how to choose the right fit.
By
Savan Kharod
Machine learning APIs make it easy to add AI capabilities like speech recognition, image analysis, and predictive insights to applications—without building models from scratch. In this guide, we’ll explore the best ML APIs, their benefits, and how they simplify AI integration for developers.
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.
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.
APIs power modern apps, but outdated docs, debugging errors, and security risks slow teams down.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.
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.
API testing is essential for ensuring reliability, but should you stick with traditional test automation or adopt AI-driven testing? This article breaks down the key differences, pros and cons, and tools to help you choose the best approach for your API testing strategy.
