Goose
by
Automates engineering tasks by installing, executing, editing, and testing code using any large language model, providing end‑to‑end project building, debugging, workflow orchestration, and external API interaction.
Goose Overview
What is Goose about?
Goose is a local, extensible AI agent that goes beyond code suggestions. It can build projects from scratch, run and debug code, orchestrate complex workflows, and interact with external services autonomously, leveraging any LLM and integrating with MCP servers.
How to use Goose?
- Installation – Follow the Quickstart or Installation docs (https://block.github.io/goose/docs/getting-started/installation) to install the desktop app or CLI.
- Configuration – Specify one or more LLM providers in the configuration file to enable multi‑model selection for cost‑performance balancing.
- Execution – Invoke Goose from the command line (e.g.,
goose run <task>), or use the desktop UI to issue natural‑language commands. - Integration – Connect Goose to your MCP server by providing the server address and authentication token in the settings.
Key Features of Goose
- Full‑stack development automation: write, compile, run, test, and debug code without manual intervention.
- LLM‑agnostic: works with any LLM; supports multi‑model configurations.
- MCP integration: seamless communication with Model Context Protocol servers.
- CLI & desktop UI: flexible interaction modes for developers.
- Extensible plugins: add custom actions, API connectors, and workflow steps.
- Community & support: Discord, YouTube, LinkedIn, Twitter/X, Bluesky, Nostr channels.
Use Cases of Goose
- Rapid prototyping – Generate a complete project skeleton from a high‑level description.
- Legacy code modernization – Analyze, refactor, and test existing codebases automatically.
- CI/CD automation – Orchestrate build, test, and deployment pipelines via natural language commands.
- Educational tooling – Provide step‑by‑step coding assistance for learners.
- API integration – Automate calls to external services and handle responses within workflows.
FAQ
Q: Does Goose require a specific LLM? A: No, Goose is LLM‑agnostic and can work with any provider you configure.
Q: Can I run Goose on Windows, macOS, and Linux? A: Yes, the desktop app and CLI are cross‑platform.
Q: How does Goose interact with MCP servers? A: Configuration files let you specify the MCP server URL and API key; Goose then uses the protocol for context sharing and task coordination.
Q: Is there a free tier? A: Goose itself is open source under Apache 2.0. Costs depend on the LLM services you connect.
Q: Where can I get help? A: Join the Discord community, check the documentation site, or follow the official YouTube channel for tutorials.
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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Goose's Information
- Author
- block
- Category
- Development Tools
- Language
- Rust
- License
- Apache License 2.0
- Stars
- 18,878
- Updated
- 2 days ago
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