Bitrise

Bitrise MCP Server

The Bitrise MCP server bridges the gap between continuous‑integration workflows and AI assistants. It exposes the full breadth of Bitrise’s REST API—apps, builds, artifacts, and more—to any MCP‑compatible client. Developers can now ask an AI to trigger builds, inspect build logs, or download artifacts without leaving their IDE or chat interface. This tight integration turns routine CI/CD operations into conversational tasks, freeing time for higher‑level design and debugging.

At its core the server is a thin wrapper around Bitrise’s API, authenticating with a personal access token and translating API calls into tool invocations. Each Bitrise endpoint becomes an AI‑ready tool with well‑defined parameters, return types, and clear documentation. Because the server follows the MCP specification, it can be dropped into any ecosystem that supports the protocol—Claude Desktop, VS Code Copilot Chat, Cursor, or Claude Code—without custom adapters. The result is a single, consistent interface for all CI/CD interactions, regardless of the surrounding development environment.

Key capabilities include:

• Full API coverage – From listing apps and branches to initiating pipelines and retrieving artifacts, every public Bitrise endpoint is available as a tool.
• Secure token handling – The server accepts the API token via environment variables or input prompts, ensuring credentials never leak into logs.
• Rich metadata – Tool definitions include parameter descriptions, example values, and response schemas, enabling the AI to craft precise queries.
• Extensible configuration – Clients can supply workspace tokens or custom arguments, allowing fine‑grained control over which Bitrise projects are exposed.

Typical use cases span the entire CI/CD lifecycle:

1. On‑demand builds – A developer asks the AI to “run a nightly build for app X,” and the assistant triggers the pipeline, returning a link to the console output.
2. Artifact retrieval – During code reviews, an AI can fetch a signed IPA or APK directly into the editor, streamlining QA workflows.
3. Build diagnostics – The assistant can query failed build logs and suggest troubleshooting steps, reducing mean time to resolution.
4. Pipeline monitoring – In a team chat, the AI can report on pending or running pipelines, keeping everyone aligned without leaving the conversation.

Because it adheres to MCP, the Bitrise server plugs seamlessly into any AI‑augmented workflow. It transforms static CI/CD operations into dynamic, conversational actions, delivering a powerful productivity boost for developers who rely on Bitrise to ship code quickly and reliably.