Naoki Kuroda

As AI-powered software development rapidly proliferates, new challenges have emerged that traditional development and deployment processes cannot adequately address. The unpredictable nature of AI models, high costs, and potential risks necessitate more cautious and controllable release strategies.

In this context, OpenFeature, a standardization project for feature flags, is playing an increasingly important role in the safe and efficient deployment of AI products.

Feature flags have revolutionized how we deploy and test software, but managing them often requires context switching between multiple tools and interfaces. Today, we're excited to announce the Bucketeer MCP Server, a Model Context Protocol implementation that brings comprehensive feature flag management directly into your AI-assisted development workflow.

Feature flags have become essential for modern software development, enabling teams to deploy code safely, test features with specific user segments, and roll out changes gradually. To address the challenge of vendor lock-in when switching between different feature flag providers, we're excited to announce OpenFeature support for the Bucketeer Go SDK.

As feature flag management becomes increasingly crucial for modern software development, having quick access to comprehensive documentation can make the difference between smooth deployments and troubleshooting headaches. Today, I'm excited to share how I built a locally running Model Context Protocol (MCP) server that brings Bucketeer's entire documentation directly into AI assistants like Claude and Cursor.