Overview

Gotask‑MCP is a lightweight Model Context Protocol server that bridges generative AI assistants with the popular task runner (go‑task). It exposes two simple yet powerful tools: one that lists all tasks defined in a project's , and another that executes a chosen task by name. By providing these capabilities over MCP, the server lets AI agents—such as those running in Cursor IDE—to trigger routine development workflows directly from conversational prompts, eliminating the need for manual terminal interaction.

Why It Matters

In modern software projects, repetitive operations like linting, formatting, unit testing, and deployment are often encapsulated as tasks in a . Developers spend valuable time toggling between code editors and terminal windows to run these commands. Gotask‑MCP turns the AI assistant into a first‑class developer tool, enabling it to read the project’s context (via the working directory path) and invoke tasks on demand. This integration reduces friction, keeps developers in a single environment, and ensures that AI‑driven suggestions can be immediately validated or executed.

Key Features

• Contextual Task Discovery – The server reads the in the supplied directory and returns a comprehensive list of available tasks, allowing agents to understand what operations can be performed.
• Dynamic Task Execution – A second tool accepts a task name and runs it within the project’s isolated environment, capturing output for the agent to report back.
• Isolation and Safety – The server runs in a sandboxed process, preventing accidental modifications to the host system while still having full access to the project files.
• MCP‑Friendly Design – All interactions follow the MCP specification, making it easy to plug into any compliant client without custom adapters.

Use Cases

• Automated QA – An AI assistant can prompt the user to run all tests before a pull request, then report failures directly in the chat.
• Code Refactoring – After suggesting a refactor, the agent can run formatting or linting tasks to ensure style compliance.
• CI/CD Orchestration – Agents can trigger deployment pipelines defined in , providing real‑time status updates.
• Learning and Documentation – New contributors can ask the assistant to run example tasks, receiving step‑by‑step guidance.

Integration Flow

1. Client Setup – The MCP client (e.g., Cursor IDE) starts the Gotask‑MCP server with a command that specifies the working directory.
2. Contextual Rule – A rule file instructs the AI agent to provide the current project path when invoking the tools.
3. Tool Invocation – The agent calls either list tasks or run task, passing the directory path.
4. Execution & Feedback – The server performs the action, streams results back to the agent, which then formats and presents them to the developer.

Unique Advantages

Unlike generic shell execution tools, Gotask‑MCP is tightly coupled to the ecosystem. It understands task dependencies, variable interpolation, and environment configuration out of the box, ensuring that tasks run exactly as a developer would. This specialization reduces errors and aligns AI actions with established project workflows, making it an indispensable component for any development environment that relies on automation.