Goose Review 2026 - Features, Pricing & Alternatives

About Goose

TL;DR·

4.3/5

Goose is Block's open-source AI agent for software engineering tasks, built in Rust and released under the Apache 2.0 license. It runs locally on your machine, plugs into any LLM provider via MCP, and can autonomously edit code, run shells, and call APIs - all without per-seat licensing.

Editor's Verdict

“Goose is the most credible open-source alternative to Cursor and Claude Code, particularly for teams that want to own their infrastructure and avoid per-seat SaaS fees. Block's heavy backing and broad MCP support make it a safe long-term bet for tinkerers and enterprises alike.”

4.3/5

What is Goose?

Overview

Goose is the open-source coding agent from Block, the company behind Square, Cash App, and Tidal. Released in early 2025 and accelerated under the codename Honk in late 2025, Goose is designed for developers who want a Cursor-style agent without the SaaS lock-in. It is written in Rust, distributed as a single binary, and licensed under Apache 2.0, which means you can self-host it, fork it, or embed it in your own tooling without paying anyone.

The project has grown quickly thanks to Block's heavy investment - the company uses Goose internally across its 13,000-person engineering org - and the broader open-source community that has rallied around the Model Context Protocol (MCP) standard, which Goose was an early adopter of.

Core Features

Goose is fundamentally an agent runtime. You give it a task, and it plans, executes, and iterates using whatever tools and models you have configured. Out of the box it can read and write files, run shell commands, browse the web, and invoke any tool exposed via MCP. Because MCP is now a widely supported standard, Goose can plug into databases, GitHub, Slack, Jira, Linear, and hundreds of other services without custom adapters.

The agent supports any model provider, including Anthropic Claude, OpenAI, Google Gemini, Groq, Ollama for local models, and open-router gateways. This provider-agnostic design is the main differentiator versus closed tools like Cursor or Claude Code - you bring your own keys and pay your own model costs at API rates rather than paying a flat per-seat license on top of model usage.

Goose runs in two surfaces: a CLI for terminal-first developers and a desktop app with a chat-style UI. Both share the same underlying agent runtime, so a session started in the CLI can be resumed in the desktop app. Sessions are persistent and can be shared across machines.

Extensions are first-class. The community has built dozens of MCP-compatible extensions for common workflows - database access, browser automation, Kubernetes management, and more - and writing your own extension is straightforward.

Pricing Analysis

Goose itself is completely free. The cost you pay is for the underlying LLM API calls to whichever provider you choose. For developers already paying for Anthropic, OpenAI, or running local Ollama models, Goose adds zero incremental cost. This makes it dramatically cheaper than Cursor or Copilot for heavy users - a single Claude API key can fuel an entire team using Goose.

Block does not offer a managed Goose service today. Everything is self-run on your laptop or your own infrastructure.

Who Should Use Goose

Goose is a strong fit for developers who already pay for LLM API access and want a flexible, scriptable agent without per-seat licensing. It is particularly good for teams with strict data-residency requirements who need to run everything locally or in their own cloud, and for tinkerers who want to compose their own agent workflows from MCP building blocks.

It is less suited for developers who want a polished out-of-the-box editor experience with autocomplete - Goose is an agent first, not an editor. Pair it with VS Code, Zed, or Neovim for the editing surface.

Pros

Fully open-source under Apache 2.0 with no per-seat licensing or vendor lock-in
Provider-agnostic - works with Anthropic, OpenAI, Gemini, Groq, Ollama, and any OpenAI-compatible endpoint
Native MCP support means hundreds of extensions for databases, browsers, dev tools, and SaaS apps
Both CLI and desktop UI share one runtime, so sessions are portable across surfaces
Backed by Block (Square, Cash App), which dogfoods Goose across 13,000+ engineers

Cons

Bring-your-own-key model means you handle billing, rate limits, and provider outages yourself
No managed cloud service - everything runs locally or on your own infrastructure
Less polished editor surface than Cursor or Windsurf - you pair it with your own editor for autocomplete

How to Use Goose

1
Install Goose
Install via Homebrew on macOS (`brew install goose`), or grab a release binary for Linux and Windows from the GitHub releases page.
2
Configure a Model Provider
Run `goose configure` and choose a provider - Anthropic, OpenAI, Gemini, Groq, or local Ollama. Paste your API key once and it is stored locally.
3
Start a Session
Launch the CLI with `goose session` or open the desktop app. Describe your task in plain English.
4
Add Extensions
Install MCP extensions to expand what Goose can do - GitHub, Slack, Linear, PostgreSQL, browser automation, and more.
5
Iterate
Goose shows each tool call before executing potentially destructive actions, so you stay in control. Approve, reject, or redirect at any step.

Key Features of Goose

AI Capabilities

Multi-Provider LLM Support

Works with Anthropic, OpenAI, Gemini, Groq, Ollama, and any OpenAI-compatible endpoint

Autonomous Agent Loop

Plans, executes, and iterates on multi-step coding tasks with optional approval gates

Built-in Shell and File Tools

Read, write, and edit files; run shell commands and manage processes natively

Block-backed Roadmap

Maintained by Block engineering with 13,000+ internal users dogfooding the product

Integration

MCP Extension Ecosystem

Hundreds of community-built MCP extensions for databases, browsers, GitHub, Slack, and more

Editor/IDE

CLI and Desktop App

Same agent runtime exposed through a terminal CLI and a desktop chat UI - sessions are portable

Persistent Sessions

Sessions are stored locally and can be resumed or shared across machines

Privacy & Security

Local Model Support

First-class Ollama integration means you can run Llama, Mistral, or Qwen entirely locally

Open Source (Apache 2.0)

Fully open-source - inspect, fork, embed, or self-host without restrictions

Tool Approval Controls

Configure whether Goose asks before destructive operations or runs autonomously

View all Goose features

Key Specifications

Attribute	Goose
Vs	[object Object],[object Object],[object Object]
Strengths	Fully open-source (Apache 2.0),Provider-agnostic model support,Strong MCP extension ecosystem,Local model support via Ollama,Backed by Block with heavy internal use
Weaknesses	No built-in editor or autocomplete,No managed cloud service,Documentation lags commercial competitors,You manage model billing and rate limits

Integrations

AI Model

Anthropic ClaudeOpenAIGoogle Gemini

Local Model

Ollama

Version Control

GitHub

Communication

Slack

Database

PostgreSQL

Extension Standard

MCP Servers

Pricing

Starting from $Free (open-source)

Free tier available

Goose is free and open-source under Apache 2.0. You pay only for the LLM API calls of whichever provider you choose to use.

Open Source

$0/ month

Apache 2.0 license
Bring your own LLM provider keys
CLI and desktop app
MCP extension support
Cross-platform (macOS, Linux, Windows)
Persistent sessions
Local Ollama support

Pricing details sourced from the vendor website and may differ. Please confirm before purchasing.

Goose Alternatives

Top 5 alternatives for 2026

Google AI Studio

Web-based IDE for prototyping with Google’s generative AI models.

5.0

AI Code Assistants

Cursor

AI-native code editor built on VS Code

4.6

AI Code Assistants Vibe Coding

Google Antigravity

Google's agent-first IDE powered by Gemini 3

4.5

AI Code Assistants

Codestral

Mistral's code-specialized LLM

4.5

AI Code Assistants

Zed

High-performance Rust editor with built-in AI

4.5

AI Code Assistants

View all Goose alternatives

Goose FAQs

Is Goose really free?+

Yes. Goose is open-source under Apache 2.0 with no per-seat licensing. You only pay for the LLM API calls to whichever provider you configure - Anthropic, OpenAI, or a local Ollama model.

What models does Goose support?+

Goose is provider-agnostic. It supports Anthropic Claude, OpenAI GPT, Google Gemini, Groq, Ollama (for local models), and any OpenAI-compatible endpoint. You bring your own API keys and choose per session.

How does Goose compare to Cursor?+

Cursor is a polished VS Code-based editor with a built-in subscription, while Goose is an open-source CLI and desktop agent that pairs with your existing editor. Goose has no per-seat fee and is provider-agnostic, but Cursor's autocomplete and editor UX are more refined.

What is MCP and why does Goose use it?+

Model Context Protocol (MCP) is an open standard for connecting AI agents to tools, data, and services. Goose was an early adopter, which means hundreds of community-built MCP extensions for databases, browsers, GitHub, Slack, and more work with Goose out of the box.

Can I run Goose with local models?+

Yes. Goose has first-class Ollama support, so you can run any local model - Llama, Mistral, Qwen, or Code Llama - and keep all data on your machine. Quality depends on the local model's capabilities.

Who is behind Goose?+

Goose is built and maintained by Block, the public company behind Square, Cash App, and Tidal. Block uses Goose internally across its engineering org of 13,000+ people, which gives the project significant ongoing investment.

Does Goose work on Windows and Linux?+

Yes. Goose ships native binaries for macOS, Linux, and Windows. Both the CLI and desktop app are cross-platform.

Can Goose run shell commands and edit files?+

Yes. Goose has built-in tools for reading and writing files, running shell commands, and managing processes. You can configure approval levels so it asks before destructive operations or runs fully autonomously for trusted tasks.