Goose
by
Automates engineering tasks on local machines, executing code, building projects, debugging, orchestrating workflows, and interacting with external APIs using any LLM.
Goose Overview
What is Goose about?
Goose is a local, extensible AI agent that automates complex development tasks from start to finish. It goes beyond code suggestions by building projects from scratch, executing and testing code, debugging failures, and orchestrating multi‑step workflows.
How to use Goose?
- Installation – Follow the Quickstart or Installation guides on the documentation site to install the desktop app or CLI.
- Configuration – Choose any LLM (OpenAI, Anthropic, etc.) and optionally configure multi‑model setups for cost‑performance balance.
- Execution – Invoke Goose via the CLI or desktop UI, providing a high‑level instruction (e.g., "create a Go microservice"), and let it draft, run, and refine code autonomously.
- Integration – Connect Goose to MCP servers, external APIs, or CI pipelines to extend its automation capabilities.
Key features of Goose
- Multi‑LLM support – Works with any LLM and allows multi‑model configurations.
- Full‑stack automation – From project scaffolding to execution, debugging, and testing.
- Extensible architecture – Plug‑in system for custom commands, tools, and API integrations.
- Desktop & CLI – Available as a graphical desktop application and as a command‑line interface.
- MCP server integration – Seamlessly interacts with Model Context Protocol servers for advanced workflows.
Use cases of Goose
- Rapid prototyping of new services or libraries.
- Automated refactoring and codebase modernization.
- Continuous integration/continuous deployment (CI/CD) augmentation.
- Debugging complex runtime failures without manual intervention.
- Orchestrating multi‑step data pipelines or infrastructure tasks.
FAQ from the Goose community
Q: Can Goose work with my private LLM deployment? A: Yes, Goose can be configured to point to any self‑hosted LLM endpoint.
Q: Do I need an internet connection for all tasks? A: Only when the chosen LLM is cloud‑based; local LLMs run entirely offline.
Q: How does Goose handle sensitive code or credentials? A: Goose runs locally, and you can configure environment variables and secrets that stay on your machine.
Q: Is there a way to extend Goose with custom commands? A: The extensible plug‑in system lets you add new tools, scripts, or API connectors.
Q: What platforms are supported? A: Goose provides binaries for macOS, Linux, and Windows, plus a cross‑platform CLI.
Goose's README
codename goose
a local, extensible, open source AI agent that automates engineering tasks
goose is your on-machine AI agent, capable of automating complex development tasks from start to finish. More than just code suggestions, goose can build entire projects from scratch, write and execute code, debug failures, orchestrate workflows, and interact with external APIs - autonomously.
Whether you're prototyping an idea, refining existing code, or managing intricate engineering pipelines, goose adapts to your workflow and executes tasks with precision.
Designed for maximum flexibility, goose works with any LLM and supports multi-model configuration to optimize performance and cost, seamlessly integrates with MCP servers, and is available as both a desktop app as well as CLI - making it the ultimate AI assistant for developers who want to move faster and focus on innovation.
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