Tugboat MCP Server

Overview of Tugboat MCP Server

The Tugboat MCP Server bridges AI assistants, such as Claude, with the Tugboat API through the Model Context Protocol (MCP). By exposing Tugboat’s project, preview, and repository resources as standardized MCP entities, the server resolves a common pain point for developers: accessing and manipulating external tooling without writing custom integrations. Instead of manually crafting HTTP requests or maintaining separate SDKs, developers can leverage the MCP interface to issue high‑level commands that the AI assistant translates into concrete API calls.

At its core, the server offers a rich set of actions that mirror Tugboat’s native capabilities. Users can list projects, create new previews, trigger builds, refresh or delete existing previews, and search across resources. The server also provides log access for each preview, enabling developers to inspect build outputs or troubleshoot failures directly from the AI chat. These functions are exposed as MCP tools, allowing an assistant to invoke them with natural language prompts while the server handles authentication and API interaction behind the scenes.

Integration is seamless. The Tugboat MCP Server supports both standard input/output (stdio) and HTTP transports, making it compatible with desktop clients like Claude Desktop as well as programmatic environments. Authentication is handled via a single API key supplied through environment variables, ensuring that the server remains stateless and secure. When configured in Claude Desktop, a familiar hammer icon appears in the toolbar, signaling that Tugboat tools are available. Developers can then ask the assistant to perform complex workflows—such as listing all previews for a project or triggering a rebuild—and receive instant, context‑aware responses.

Real‑world scenarios that benefit from this server include continuous deployment pipelines where an AI assistant can monitor preview status, automatically roll back on failures, or suggest optimizations. QA teams can use the server to generate new previews on demand and compare them against baseline logs, all within a single conversational interface. Moreover, because the server implements MCP’s standardized resource and tool contracts, it can be easily swapped out or extended to support additional Tugboat features without changing the assistant’s code.

Unique advantages of the Tugboat MCP Server lie in its modular architecture and built‑in transport flexibility. The separation between core logic, resources, tools, and authentication layers means that contributors can add new capabilities—such as custom preview actions or advanced search filters—without touching the core. Additionally, the ability to run the server locally via stdio eliminates network latency and simplifies development workflows, while the HTTP transport option opens doors to cloud‑hosted deployments for larger teams. In sum, Tugboat MCP Server empowers developers to harness the full power of Tugboat from within AI assistants, streamlining operations and accelerating delivery cycles.