
goose
goose is a free, open source AI agent that runs on your own machine as a desktop app, CLI or API. Written in Rust, it connects to 70+ MCP extensions and 15+ model providers for coding, research and automation.
What is goose?
goose is a general-purpose AI agent that runs on your own machine rather than in a browser tab. It is open source under the Apache 2.0 licence and written in Rust, and it comes in three shapes: a native desktop application for macOS (Apple Silicon and Intel), Linux (DEB, RPM and Flatpak) and Windows, a full command-line interface, and an API you can embed. The home page reports 45k+ GitHub stars, 500+ contributors and 70+ extensions. Because it executes locally, goose has direct access to your development environment: it runs shell commands, edits files and drives the tools you already use. Its reach is extended through the Model Context Protocol (MCP), the open standard goose was among the first to adopt. Extensions cover databases, APIs, browsers, GitHub, Google Drive and dozens more, and six ship built in: Developer, Computer Controller, Memory, Todo, Extension Manager and Chat Recall. With MCP Apps, an extension can render interactive interfaces - buttons, forms, visualisations - inside goose Desktop. Two ideas structure day-to-day use. Recipes turn a working session into a portable YAML file carrying instructions, extensions, parameters and sub-recipes, so a workflow can be shared with a team or executed in CI. Subagents run independent tasks in parallel, keeping the main conversation clean while code review, research or file processing happens alongside it. Model choice stays yours. goose supports 15+ providers, among them Anthropic, OpenAI, Google, Azure, Amazon Bedrock, OpenRouter and local runtimes such as Ollama. Through the Agent Client Protocol it also acts as an ACP server for Zed, JetBrains and VS Code, and can use Claude Code or Codex as providers, reusing an existing subscription instead of an API key. Security is treated as a feature rather than an afterthought: prompt injection detection, per-tool permissions, a sandbox mode and an adversary reviewer that watches for dangerous actions. Project context comes from .goosehints or AGENT.md files, and configuration lives in ~/.config/goose/. Governance changed hands in April 2026, when Block donated the project to the Agentic AI Foundation at the Linux Foundation, alongside Anthropic's MCP and OpenAI's AGENTS.md. The repository now lives at github.com/aaif-goose/goose, under vendor-neutral, community governance.
What it does
- Write, refactor and review code, and work through issues raised in CI
- Run shell commands, edit files and automate tasks directly on your machine
- Connect 70+ MCP extensions to reach databases, APIs, browsers, GitHub or Google Drive
- Capture a working session as a shareable YAML recipe and replay it in CI
- Launch parallel subagents for code review, research or file processing
- Choose your LLM among 15+ providers, including models running entirely on your own hardware
- Handle non-code work: research, writing, automation and data analysis
When to use goose / When not to
A quick filter to help you decide if goose is the right fit.
When to use goose
- Developers who want a general-purpose agent running locally, with direct access to their shell, their files and their development environment
- Platform and DevOps teams looking to capture repeatable workflows as portable YAML recipes and run them in CI
- Engineers who want to avoid model lock-in and switch freely between 15+ LLM providers, including fully local ones such as Ollama, LM Studio or Docker Model Runner
- Organisations that need their own branded agent, through custom distributions and an extension allowlist restricting which MCP servers can be installed
- Researchers, writers and analysts comfortable with a desktop tool, for the non-code work the project explicitly claims: research, writing, automation and data analysis
When not to use goose
- Teams looking for a turnkey hosted service: goose is a binary you install and configure yourself, with no web app and no account held by the publisher
- Buyers who need a contractual framework: the domain publishes no terms of service, no privacy policy and no legal notice
- Organisations with strict data protection procurement: no DPA, no subprocessor list, no Article 27 representative and no GDPR claim are published
- Users who expect an all-inclusive price: goose ships no model of its own, so the API key or subscription of the LLM provider you choose stays at your expense
- Anyone who needs commercial support or a mobile-first product: help runs through Discord and GitHub with no published email address, and the iOS client is described by the publisher as still early
How to use goose
A typical end-to-end flow, from setup to results.
- Install the desktop app: download the build for your platform, or on macOS run brew install --cask block-goose
- Or install the command-line interface with the one-line download script documented on the installation page
- Pick the right package for your system: separate archives for Apple Silicon and Intel on macOS, DEB, RPM or Flatpak on Linux, a zip on Windows with Git Bash, MSYS2, PowerShell or WSL for the CLI
- On Windows, add goose to your PATH before running goose configure, and decline the keyring if it returns an error
- Configure a provider on the Desktop welcome screen or with goose configure: an API key, a ChatGPT subscription, Tetrate Agent Router Service, OpenRouter or another endpoint
- Choose a model from the list returned by that provider
- Start a session and hold a continuous conversation with goose about the task at hand
- Add MCP extensions through goose configure, then Add Extension, or from the extension directory on the site
- Give project context with a .goosehints or AGENT.md file at the root of your repository, and set defaults in config.yaml and profiles.yaml under ~/.config/goose/
- If you need remote access, run goose serve with a host, a port, TLS and a GOOSE_SERVER__SECRET_KEY, then point goose Desktop at that instance
Pros & Cons
Pros
- Free and open source under Apache 2.0, with no paid tier and no usage limit imposed by the project itself
- No model lock-in: 15+ providers, including inference running entirely on your own hardware
- Local execution: conversations and interactions are stored on your machine, in both the CLI and the desktop app
- Vendor-neutral governance at the Agentic AI Foundation of the Linux Foundation, with 500+ contributors and 45k+ GitHub stars
- Telemetry is anonymous, opt-in and switchable, and excludes conversations, code, tool arguments and personal data
- Unusual security depth for an agent: sandbox mode, per-tool permissions, prompt injection detection and an adversary reviewer
- Three surfaces (desktop, CLI, API) plus a remote server mode, and the freedom to fork and rebrand through custom distributions
Cons
- No privacy policy, no terms of service and no legal notice anywhere on the domain
- No postal address and no email address published: support runs through Discord and GitHub only
- No DPA, no subprocessor list and no GDPR claim, which rules the tool out of some procurement processes
- The real cost is shifted onto the LLM provider and is never quantified by goose
- Technical installation: terminal, PATH handling, keyring quirks on Windows and per-platform prerequisites
- Licence stated inconsistently: the llms.txt file says MIT on one line and Apache 2.0 on another, while the home page shows Apache 2.0
- Migration to the foundation was still in progress at review time, with broken links and redirects acknowledged by the publisher; mobile clients are early and the extension directory does not render without JavaScript
Pricing & Plans
goose is free. The software is published as open source under the Apache 2.0 licence, there is no paid plan, no subscription and no pricing page on the site - a sitemap of 317 URLs contains none. There is therefore no entry price and no currency to report. The only cost of running goose is indirect and external: the API key or subscription of the LLM provider you choose, billed by that provider. The Providers page documents a Using goose for Free route listing endpoints reachable at no cost, among them Groq, EmpirioLabs AI, FuturMix, Novita AI, Routstr, SayGM and Google Gemini, alongside local models that cost nothing beyond your own hardware.
- a single edition with every feature included
- no paid tier
- no enterprise edition and no pricing page on the site
Data, GDPR & hosting
A consolidated view of how goose handles your data.
GDPR overview
The site makes no GDPR claim for goose. Across the pages collected, the single occurrence of the word GDPR describes Scaleway, one of the third-party LLM providers listed as a supported endpoint: it commits Scaleway, not goose. No privacy policy, no terms of service and no legal notice exist on the domain, and a sitemap of 317 URLs confirms these pages are absent rather than merely hard to find. There is no Article 27 representative, no data protection officer, no data processing agreement, no subprocessor list and no contact email address of any kind. What exists is architectural rather than contractual: goose runs locally, conversations stay on the machine, and the only publisher-side collection is anonymous telemetry you must explicitly opt into at first launch.
Who owns the data?
goose runs on your own machine, and the documentation states that all conversations and interactions, in both the CLI and the desktop app, are stored locally. In practice you hold everything: session history, generated files and the configuration in ~/.config/goose/. The publisher applies no ownership clause to any of it, for a simple reason - no terms of service and no privacy policy are published on the domain, so no contractual text defines ownership, licence or reuse. The only publisher-side collection is an optional anonymous telemetry stream. Anything you send to the LLM provider you connect falls under that provider's own policy, not goose's.
Reuse rights
No terms of service exist on the site, so nothing restricts what you do with your sessions, your outputs or the files goose produces: they sit on your machine and are yours to reuse without asking anyone. The Apache 2.0 licence covers the software itself, not the content you generate with it, and it also allows you to fork and redistribute goose. On the publisher's side, the only documented collection is anonymous telemetry, opt-in at first launch, whose stated purpose is product improvement. Six categories are listed: operating system, version and architecture; goose version and installation method; provider and model in use; extension names and tool usage counters; session metrics such as duration, number of interactions and token counts; and error types such as rate_limit or auth, without detail. It excludes conversations, code, tool arguments, error messages and personal data, and can be switched off at any time. The documentation warns separately that, depending on the LLM you use, your prompts and the information goose accesses may be sent to that provider and fall under its own retention and privacy policies.
Data retention & training
Hosting summary
There is no publisher-side hosting to describe: goose runs on the user's own machine. The documentation states that all conversations and interactions, in both the CLI and the desktop app, are stored locally, and configuration lives in ~/.config/goose/ through config.yaml and profiles.yaml. No hosting country, region or jurisdiction appears anywhere on the site, which follows from a locally executed tool rather than from an omission. The documentation site itself is served by GitHub Pages behind Fastly, on an anycast address routed from the United States, but that concerns the docs, not user data. Two paths do send data off the machine. First, every request to the LLM provider you configure, which falls under that provider's own jurisdiction and policies. Second, two optional modes: a remote instance started with goose serve, hosted on infrastructure you choose and protected by TLS and a shared secret, and mobile access, which the publisher describes as passing through a Cloudflare tunnel when you enable it.
Things to keep in mind
Risks and trade-offs to weigh before adopting goose.
- The agent runs shell commands and edits files on your machine: set tool permissions and sandbox mode before letting it work unattended
- The CLI installs through a script piped from the network into a shell: read the source first, as with any script you execute that way
- Whatever you send to the LLM provider you configured leaves your machine and falls under that provider's retention and privacy policy, not goose's
- No terms of service, no privacy policy and no legal notice exist on the domain, and no email or postal address is published: there is no contractual recourse and nobody identified to contact
- The licence is stated inconsistently, MIT on one line of the llms.txt file against Apache 2.0 on another and on the home page: clarify before redistributing or embedding the code
- The goose-docs.ai domain was registered on 30/03/2026 and first archived on 06/04/2026: these dates describe the documentation site, not the project, whose blog goes back to November 2024
- An agent this capable invites over-delegation: read the code and the shell actions it proposes instead of approving them by reflex, or you inherit changes nobody reviewed
Setup & Integrations
Technical difficulty
Moderate, and technical rather than lengthy. The desktop app installs by download or with a single Homebrew command; the CLI takes one curl command followed by goose configure. No account is created with the publisher. The real hurdle is obtaining and configuring an LLM provider key. Windows adds friction: the PATH must be completed by hand and the keyring declined if it errors. Linux offers three package formats depending on the distribution. Running the remote server with TLS is a system administrator task. A developer will be up in minutes; a non-technical user will need help.
Deployment
Integrations
Supported languages
Behind goose
Fundraising
Social
Resources
All the official URLs gathered for verification and reference.
Frequently asked questions
Is goose free?
Which operating systems does goose support?
Which AI models can I use with goose?
Can I use goose without sending anything to a cloud service?
Does goose collect my conversations?
How do I turn telemetry off?
Who publishes goose?
Is there an API?
Is there a mobile app?
How do I get support?
Should you pick goose?
goose brings together three things that rarely come as a package: it is entirely free, genuinely open source under Apache 2.0, and it runs on your own machine rather than on someone else's servers. Model choice stays with you, from an Anthropic or OpenAI key down to a local Ollama model that never leaves your hardware, and conversations are stored locally in both the desktop app and the CLI. Around that core sits a mature ecosystem: 70+ MCP extensions, YAML recipes that make a workflow portable and runnable in CI, parallel subagents, and security controls - sandbox, per-tool permissions, prompt injection detection, adversary reviewer - that remain unusual among agents. Governance is equally solid: since April 2026 the project belongs to the Agentic AI Foundation at the Linux Foundation, with 500+ contributors behind it. The main reservation concerns not the product but what the site does not publish. No terms of service, no privacy policy, no legal notice, no postal address and no email address exist anywhere on the domain, and the sitemap confirms those pages are simply absent. For an individual developer this changes little; for a legal or procurement team it is a real obstacle, since there is nothing to sign and nobody identified to write to. Support runs through Discord and GitHub alone. The natural audience is developers and technical teams, though the project explicitly claims non-code uses such as research, writing and data analysis. Activity is clear, with a blog running to July 2026, but the migration to the foundation was still under way at review time. Treat goose as a powerful local tool to configure carefully, not as a contractually framed enterprise service.
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