Open source AI coding agent with a desktop app, CLI, and 70+ MCP extensions across 15+ LLM providers, backed by the Linux Foundation
- Category
- Coding agents
- From
- Free (self-hosted)
- Pricing model
- free
- Free tier
- Yes
- Deployment
- Self-host
- Interface
- CLI
- Open source
- Yes
- Public API
- Yes
- Model / LLM
- 15+ providers including Anthropi…
Facts re-verified
On this page
Our verdict
Goose is a genuinely open, provider-agnostic alternative to closed coding agents: install it free under Apache 2.0, point it at any of 15+ LLM providers, and extend it with 70+ MCP tools rather than being stuck with one vendor's model and roadmap.
Backing from the Linux Foundation's Agentic AI Foundation and a community of 500+ contributors gives it more institutional weight than a typical side project.
The tradeoff is that Goose is a toolkit, not a managed product. There's no bundled subscription or support line, users configure their own provider and absorb that provider's costs and rate limits directly, and evaluation currently relies almost entirely on the vendor's own documentation. For developers comfortable managing their own API keys and provider choices, that's a fair exchange for the flexibility it buys.
What is Goose?
Goose is an open source AI coding agent distributed as a native desktop app for macOS, Linux, and Windows, plus a command line interface. It automates software development tasks by connecting to over 70 Model Context Protocol extensions and more than 15 LLM providers.
Goose is stewarded by the Agentic AI Foundation (AAIF), a project under the Linux Foundation, and is aimed at developers who want an extensible, provider-agnostic coding agent rather than a closed SaaS tool.
What does Goose do?
Goose runs as a continuous, resumable session (goose session -r) where it plans and executes coding tasks: writing code, running commands, and calling out to extensions. Extensions connect through the Model Context Protocol, so a session can reach into tools like the built-in Computer Controller extension for webscraping, file caching, and automation, or any of the 70+ community and first-party MCP extensions.
Because Goose is provider-agnostic, a user points it at one of 15+ supported LLM backends, including Anthropic, OpenAI, Google, Ollama, OpenRouter, Azure, Bedrock, ChatGPT Codex, Claude Code CLI, and Tetrate Agent Router Service (which grants $10 in free credits on first authentication). It also exposes an API for embedding the agent into other applications, and it can run as an Agent Client Protocol (ACP) server so it operates inside Zed, JetBrains IDEs, or VS Code instead of a standalone window.
Security features include prompt injection detection, tool permission controls, and a sandbox mode, which matter because the agent is granted the ability to execute commands and call external tools on a developer's machine.
How Goose works
- Install Goose as a native desktop app (macOS, Linux, Windows) or via the CLI
- Connect an LLM provider such as Anthropic, OpenAI, or OpenRouter using an API key
- Start a session and give Goose a coding task; it plans, executes, and calls MCP extensions as needed
- Resume a prior session at any time with goose session -r, or run Goose as an ACP server inside Zed, JetBrains, or VS Code
Key features
- 15+ LLM providers
- Works with Anthropic, OpenAI, Google, Ollama, OpenRouter, Azure, Bedrock, ChatGPT Codex, Claude Code CLI, and Tetrate Agent Router Service, so teams are not locked to one model vendor.
- 70+ MCP extensions
- Connects to the coding agent's environment through the Model Context Protocol, including a built-in Computer Controller extension for webscraping, file caching, and automation.
- Desktop app and CLI
- Native desktop app on macOS, Linux, and Windows, plus a full CLI, so the same agent can run interactively or scripted.
- ACP server mode
- Runs as an Agent Client Protocol server, letting it be driven from inside Zed, JetBrains IDEs, or VS Code instead of a separate app.
- Embeddable API
- Provides an API for embedding Goose's agent behavior into other applications rather than only using the desktop or CLI front ends.
- Session security controls
- Includes prompt injection detection, tool permission controls, and a sandbox mode to constrain what an agent session can execute.
What are Goose's use cases?
- Terminal-first coding automation
- A developer installs the Goose CLI and starts a resumable session to automate repetitive coding tasks like refactors, test writing, or debugging without leaving the terminal.
- Agent inside an existing IDE
- A JetBrains, Zed, or VS Code user connects Goose as an ACP server so agent assistance appears inside the editor they already use, instead of switching to a separate desktop app.
- Embedding an agent into internal tooling
- An engineering team uses Goose's API to embed its agent behavior into an internal developer platform or CI pipeline rather than exposing the standalone app to every engineer.
- Provider cost and performance tradeoffs
- A team routes Goose through OpenRouter for access to 200+ pay-per-use models, or tries Tetrate Agent Router Service to use the $10 in free credits granted on first authentication.
Who is Goose for?
- Developers who want a free, open source coding agent instead of a paid closed-source SaaS tool
- Engineering teams that want to embed agent behavior into internal tools via API rather than use a standalone app
- IDE users on Zed, JetBrains, or VS Code who want agent capability inside their existing editor via ACP
Not forNon-technical users or teams that want a fully managed, zero-configuration coding assistant with vendor support included; Goose requires choosing, configuring, and paying for your own LLM provider separately.
What does Goose integrate with?
- Anthropic API
- OpenAI
- Ollama
- OpenRouter
- Azure OpenAI
- Amazon Bedrock
- ChatGPT Codex
- Claude Code CLI
- GitHub Copilot
- Tetrate Agent Router Service
- Zed
- JetBrains IDEs
- VS Code
- Computer Controller extension
Why use Goose?
- 45k+ GitHub stars and 500+ contributors indicate an active open source community rather than a single-vendor project
- Stewarded by the Agentic AI Foundation (AAIF) under the Linux Foundation, giving it neutral governance instead of one company's roadmap
- Supports 15+ LLM providers and 70+ MCP extensions, so teams aren't locked into a single model vendor or fixed toolset
- Apache 2.0 licensing means the code is free to install, inspect, and self-host
What are Goose's pros and cons?
What's great
- Free and open source under Apache 2.0, with no single-vendor lock-in on the tool itself
- Works with 15+ LLM providers, letting users pick models on cost or capability grounds
- Backed by the Linux Foundation's Agentic AI Foundation with a large contributor base (45k+ stars, 500+ contributors)
- Extensible via 70+ MCP extensions and usable inside popular IDEs through ACP server mode
Watch-outs
- Being self-hosted, users must bring and pay for their own LLM API keys; there is no bundled subscription covering model usage
- Getting started requires choosing and configuring an LLM provider, which adds setup friction compared with all-in-one hosted coding assistants
- No named enterprise support tier or SLA is documented, which may matter to teams used to vendor-backed SaaS agents
- Details here come from the vendor's own documentation site (goose-docs.ai) with one supporting GitHub issue in the project's own repository; independent third-party reviews of Goose are not available yet.
- No published pricing tiers exist to compare, since the product itself is free and open source; only underlying LLM provider costs vary.
Goose pricing
Free and open source (Apache 2.0)
Open source
Free (self-hosted)
See current pricing on goose-docs.ai ↗Compare Goose alternatives →
Frequently asked questions
Is Goose free to use?
Which LLM providers does Goose support?
Can Goose run inside my code editor?
Does Goose provide an API?
What extensions can Goose use?
Anything to add?
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