How to Manage Feature Flags with ConfigCat's MCP Server
In this guide, you’ll learn how to connect your AI client to ConfigCat so you can list, create, and target feature flags using natural language with ConfigCat’s MCP server.

In this guide, you’ll learn how to connect your AI client to ConfigCat so you can list, create, and target feature flags using natural language with ConfigCat’s MCP server.

The feature flagging and experimentation space is heating up fast. OpenAI’s acquisition of Statsig shows just how important feature flag management has become and signals that the industry is moving toward AI-assisted, data-driven systems that optimize every release automatically.
This isn’t just another headline in the AI news cycle. It’s a sign of where software delivery is heading: toward AI-assisted, data-heavy development workflows where every release is measured, analyzed, and optimized.
For some teams, that’s the dream. For others, it’s just another layer of complexity standing between them and shipping code.

In modern software development, feature flags are a must-have. They let teams release features gradually, run A/B tests, and control access for different user groups. But there's a common challenge: How do you keep a list of dynamic user segments (like beta testers) always up to date without manually editing the dashboard every time?
To tackle this challenge, I'll show you how to update user segments in ConfigCat dynamically, including examples of setting up and using the ConfigCat's Update Segment API, best practices for managing segment details, and tips for integrating this functionality into your development workflow.

When talking to devs in the software development community about feature flags, a question that often comes up is, “Can’t I just use environment variables for that?” It's a fair question; both can influence how an app behaves. But under the hood, they serve very different purposes. Let's break it down.

Are you considering a switch from LaunchDarkly? Whether you're looking for more flexibility, cost-efficiency, or just a smoother developer experience, ConfigCat offers a refreshingly straightforward alternative. With a built-in import tool and transparent SDKs, moving your feature flags over is quicker than you might think. In this guide, we’ll walk you through the migration process - without breaking a sweat (or your codebase).

Does it matter whether you evaluate feature flags on the backend or the frontend? The answer is yes. As you might have guessed, the frontend and backend are distinct components of software architecture—and the factors we consider when working with them, such as security and control, apply to feature flags as well.
In this article, we'll explore the pros and cons of backend and frontend feature flags and solutions to challenges you may face while working with them.

Before the open source movement, software programs were 'closed source,' meaning only software developers employed by the company could access and modify them. Outsiders were kept out through non-disclosure agreements and licenses. This exclusivity motivated the creation of the open-source movement, aiming to preserve the freedom to modify and distribute software through publicly accessible code. Today, many commercial companies actively participate in the open-source ecosystem, maintaining software that is open to the public for access and contributions. One such company supporting this effort is ConfigCat.

At ConfigCat, we've seen firsthand how feature flags help teams ship faster with less risk and build more resilient, user-friendly applications. We want more people to experience these benefits, so we've decided to officially support OpenFeature.
Our OpenFeature providers were previously developed and maintained by open-source contributors. Moving forward, we've opted to develop and maintain some providers in-house, while continuing to collaborate with open-source contributors for others.
In the upcoming sections, we'll explore how to integrate OpenFeature into a Python application that currently uses the ConfigCat Python SDK.

As the gaming industry continues to evolve, driven by technological advancement and an ever-growing demand for more immersive, engaging experiences, players no longer settle for static and predictable game worlds—they crave dynamic environments that respond and adapt to their actions in real-time.
This shift toward adaptive gaming revolutionizes development techniques, enabling developers to craft personalized gameplay as unique as the player behind the controller. At the heart of this transformation lies a powerful tool: feature flags.

Hey, Rustaceans! We developed the Rust SDK in response to a feature request from one of our customers, OneSignal. When we heard about their needs, we rolled up our sleeves and released the Rust SDK two months later. With it, you can manage feature flags like a pro—whether starting a new project or optimizing an existing app. It allows you to toggle features on and off without redeploying your code. That's right—no more redeploys every time your boss changes their mind about a button color!
With ConfigCat's feature flags, you can gradually roll out new features, rigorously test them (in a controlled environment, of course), and make changes on the fly—all directly from your dashboard! Let's dive into why this is a game-changer for your development workflow.
