Unleash Feature Flag MCP Server

The Unleash Feature Flag MCP Server bridges the gap between AI assistants and the Unleash feature‑flag platform. By exposing Unleash’s RESTful API through the Model Context Protocol (MCP), it lets AI agents like Claude or Cursor query, create, update, and inspect feature flags directly from natural‑language conversations. This eliminates the need for developers to manually craft HTTP requests or write boilerplate code, allowing them to focus on higher‑level product logic.

Why This Server Matters

Feature flags are a cornerstone of modern continuous delivery, enabling rapid experimentation, staged rollouts, and safety nets. However, managing flags through the Unleash UI or command‑line tools can become tedious when scaling to dozens of projects or integrating with automated pipelines. The MCP server solves this pain by offering a programmatic, AI‑friendly interface: developers can ask an assistant to list all flags in a project or toggle a beta feature, and the assistant will translate that request into precise API calls. This streamlines release workflows, reduces human error, and accelerates feedback loops.

Core Capabilities

• Project Discovery – Retrieve a catalog of all Unleash projects, giving assistants context about available environments.
• Feature Retrieval – List or fetch detailed metadata for any flag within a specified project, including type (release, experiment, operational, kill‑switch) and description.
• Flag Lifecycle Management – Create new flags or update existing ones, setting names, descriptions, and types on the fly.
• Granular Control – Each tool accepts project and flag identifiers, ensuring operations target the correct resource without ambiguity.

These tools are exposed as standard MCP endpoints, so any client that understands the protocol can invoke them without custom adapters.

Real‑World Use Cases

• Release Automation – A CI/CD pipeline can instruct an AI assistant to enable a new feature flag before deploying code, then verify its status afterward.
• Feature Rollout Coordination – Product managers can ask the assistant to list all flags in a “dashboard” project, review their types, and decide which ones need experimental testing.
• Incident Response – During a production outage, an engineer can quickly toggle kill‑switch flags through conversation, minimizing downtime.
• Onboarding – New team members learn the flag landscape by querying the assistant, speeding up their ramp‑up time.

Integration with AI Workflows

Because it adheres to MCP, the server fits seamlessly into existing toolchains. Developers can launch it with environment variables pointing to their Unleash instance, then configure Cursor or Claude to discover the available tools automatically. The assistant can chain multiple operations—e.g., fetch a flag, update its description, and confirm the change—all within a single dialogue. The inspector feature further allows developers to audit request/response patterns, ensuring compliance and debugging complex interactions.

Distinct Advantages

• Zero Boilerplate – No need to write custom HTTP clients; the MCP server handles authentication and request formatting.
• Unified Interface – All Unleash operations are accessible through a single, consistent set of tools.
• Security‑First – Credentials are passed via environment variables, keeping tokens out of code repositories.
• Extensibility – The server can be expanded with additional Unleash endpoints (e.g., segments, strategies) without altering client logic.

In sum, the Unleash Feature Flag MCP Server empowers developers to harness AI assistants as intelligent feature‑flag managers, accelerating delivery cycles and improving operational resilience.