--- title: "Goose" url: https://abcaitools.com/goose/ date: 2026-11-03 modified: 2026-11-03 lang: en author: "anantvijaysoni" description: "Goose is a free, open-source AI agent that runs on your computer. It can edit files, write and test code, analyse data, research topics, and automate tasks. It supports multiple AI models, local inference, and MCP extensions for connecting external tools." categories: - "AI Agents" - "Automation" - "Code Generation" - "Open Source Model" - "Productivity" tags: - "AI agent" - "AI Agents for Developers" - "AI Automation Tools" - "AI coding agent" - "AI developer tools" - "AI tools" - "AI workflow automation" - "Free AI Software" - "Goose AI" - "Goose AI Review" - "Goose Desktop" - "local AI models" - "MCP Extensions" - "Model Context Protocol" - "open source AI" image: https://abcaitools.com/wp-content/uploads/2026/11/goose.webp word_count: 2765 --- # Goose **[Goose](https://goose-docs.ai/?utm_source=abcaitools.com)** is a free, open-source AI agent that helps users automate tasks on their computers. Developed originally by Block, it can write and edit code, manage files, analyze data, run commands, and connect with external tools. Goose supports multiple AI models, local execution, and MCP extensions, making it a flexible choice for developers and anyone interested in AI-powered automation. ## What Is Goose AI? If you have ever wished that an AI assistant could do more than answer questions, **Goose** is worth exploring. It is an open-source AI agent that can work directly with files, run commands, test code, analyze data, and automate different tasks on your computer. Unlike a regular [chatbot](https://abcaitools.com/category/best-general-use-ai-tools/chatbot-ai-tools/), Goose can take action after you describe what you want to accomplish. For example, you can ask it to inspect a software project, find an error, edit the necessary files, and run tests to check whether the changes work. ![Goose AI Homepage](https://abcaitools.com/wp-content/uploads/2026/11/Goose-AI-Homepage-1024x651.webp) Goose was originally developed by Block, the company formerly known as Square. The project is now part of the Agentic AI Foundation under the Linux Foundation. It is released under the Apache 2.0 licence, which allows developers to use, modify, and distribute the software under the licence's terms. Your open source AI agent+1 Another important feature is flexibility. Goose supports multiple [AI model](https://abcaitools.com/novita-ai/) providers, including OpenAI, Anthropic, Google, Ollama, OpenRouter, and Amazon Bedrock. You can choose a model based on your budget, performance needs, and privacy requirements. The best part is that the Goose software itself is free. However, using certain AI models may require a paid subscription or API credits. ## How Does Goose AI Work? Goose connects an AI model with tools that allow it to perform real tasks. You give it an instruction, the model decides how to approach the task, and Goose uses the available tools to carry out the required steps. For example, imagine that you want to create a simple website. You could ask Goose to create the HTML, CSS, and JavaScript files, build the website, and test its main features. A typical workflow looks like this: - Give an instruction: Explain the task you want Goose to complete. - Understand the request: The connected AI model plans the work. - Use tools: Goose reads files, edits code, runs commands, or connects to external services. - Check the result: It can run tests and inspect the output when suitable tools are available. - Review the work: You check the result and approve any actions that need your permission. The exact process depends on the model, enabled extensions, and security settings. Goose is not guaranteed to complete every task correctly, so checking its output is important. Your open source AI agent+1 ## Key Features of Goose AI ### 1. Desktop App, Command Line, and API ![Getting started with goose on Windows](https://abcaitools.com/wp-content/uploads/2026/11/Getting-started-with-goose-on-Windows.webp) Goose offers different ways to work, so you do not have to use only one interface. - Desktop app: A graphical interface for people who prefer working with windows, menus, and conversations. - Command-line interface (CLI): A terminal-based option for developers who want to work directly with their projects. - API and [development tools](https://abcaitools.com/blog/mcp/): Options for integrating Goose into other applications and automated workflows. It supports macOS, Windows, and Linux. Beginners can start with the desktop app, while experienced developers may prefer the terminal. ### 2. Support for Multiple AI Models One of Goose's strongest features is that you are not restricted to a single AI company. It supports more than 15 model providers and services, including: - OpenAI - Anthropic - Google - Ollama - OpenRouter - Microsoft Azure - Amazon Bedrock The available models and setup requirements vary by provider. Some connections require API keys, while supported integrations can use eligible subscriptions. This flexibility is useful when one model performs better at coding and another is more suitable for research or general writing. You can choose the model that fits your needs instead of changing your entire workflow. Your open source AI agent+1 ### 3. Run AI Models Locally Many AI tools process requests through cloud servers. Goose also supports local model options, allowing compatible AI models to run on your own computer. For example, you can connect Goose to a supported local model through Ollama or use its documented [local inference](https://abcaitools.com/ollama-ai/) options. This approach has several advantages: - You may not need to pay per API request. - Your prompts and files can remain on your machine when the workflow uses only local components. - Some tasks can work without an internet connection. - You have more control over the model you use. However, local AI is not completely cost-free. You still need suitable hardware, electricity, storage, and time for setup. Smaller models may also be less accurate or less capable at using tools than stronger cloud models. Important: Local inference alone does not guarantee that every part of your workflow stays offline. Cloud extensions and external services may still send data over the internet. ### 4. MCP Extensions for More Capabilities Goose supports the Model Context Protocol (MCP), an open standard that allows AI applications to connect with external tools and data sources. The official project documentation lists more than 70 extensions. Depending on the extension, you can connect Goose to services and tools involving: - GitHub and software repositories - Google Drive and files - Databases - Web browsers - Developer tools - APIs and other external services For example, you could use a suitable extension to help inspect a GitHub repository or work with information stored in a connected database. Goose Desktop also supports MCP Apps, which can display interactive elements such as forms, buttons, and visualisations inside a conversation. This makes some workflows easier to use than a simple text-based exchange. Your open source AI agent+1 Keep in mind that the availability of a service depends on its extension and configuration. You may need to install and configure tools before using them. ### 5. Reusable Recipes Do you regularly perform the same task? Goose has a feature called Recipes that can help you save repeatable workflows. Recipes use YAML configuration files to store instructions, parameters, extensions, and smaller subrecipes. For example, you could create a recipe that: - Reads a folder of research notes. - Organises the information into categories. - Creates a summary. - Saves the final report in a specified location. After setting up the workflow, you can reuse it instead of writing the complete instruction every time. Recipes can also be shared with team members and used in automated environments. This is helpful for developers and businesses that want to standardise repeated tasks. ### 6. Parallel Subagents Goose can delegate separate parts of a larger task to independent subagents. Imagine that you are working on a website and want to review its code, research competing websites, and check documentation. Depending on the task and configuration, different agents can work on separate parts of the job. The main session can then bring the results together for your review. This approach may reduce the time spent on larger tasks. However, parallel agents can use additional model resources, and their results still need to be checked for accuracy and consistency. ### 7. Coding and Software Development Goose is especially useful for developers who want an [AI assistant](https://abcaitools.com/ai-fiesta/) that can work with a real project rather than simply suggest code. It can help with tasks such as: - Creating files and folders. - Editing existing code. - Finding possible bugs. - Running shell commands. - Executing tests. - Understanding unfamiliar code. - Reviewing software changes. - Automating development tasks. For example, if a website has a broken feature, you can ask Goose to inspect the relevant files, identify the likely problem, suggest a fix, and run suitable tests. The final result depends on the quality of the connected model and the tools available. Always review important code changes before deploying them to a live website. ### 8. Research, Writing, and Data Analysis Goose is not limited to programming. It can also help with everyday computer-based work. For research, you can ask it to collect information from accessible sources, organise notes, and prepare a report. With the right tools, it can analyse files and structured data, helping you understand patterns or find useful information. For writing, it can assist with drafts, summaries, documentation, and editing. You can also use it to process multiple files or turn raw information into a more organised format. Here are a few examples: | Task | How Goose can help | | ---- | ------------------ | | Research | Organise information and prepare reports | | Writing | Draft articles, summaries, and documentation | | Data analysis | Read supported files and analyse data | | File management | Inspect and edit files with appropriate permissions | | Website development | Create and test website code | | Repeated work | Run saved workflows through Recipes | Some tasks require additional extensions or scripts. Goose does not automatically have access to every website, account, file type, or online service. ### 9. Automation Through Scripts and CI Pipelines Goose can run saved workflows without requiring you to keep the desktop interface open. This is useful for developers who want to automate work through scripts or continuous integration (CI) pipelines. For example, a team could configure a workflow to review code, prepare documentation, or analyse test results as part of its development process. This feature can save time when the same task needs to be completed regularly. However, automated workflows should have clear permissions, error handling, and appropriate checks before they are allowed to change important files or systems. ### 10. Security and Permission Controls An AI agent that can edit files and execute commands needs more care than a chatbot that only generates text. Goose includes security features such as approval modes, tool permissions, sandboxing, prompt injection detection, and an adversary reviewer. These controls help reduce the risk of unwanted actions, although they cannot guarantee complete safety. Your open source AI agent+1 Before enabling an extension, check what information it can access and what actions it can perform. For example, an extension with access to a repository may be able to read or change its contents. An extension connected to a service account may also have access to information stored in that account. For safer use: - Review commands before allowing them to run. - Avoid granting unnecessary permissions. - Back up important files. - Use sandboxing where appropriate. - Never share API keys or passwords in prompts. - Be careful with instructions copied from unknown websites or files. If you use a cloud AI provider, its data handling and retention policies also matter. Read those policies before processing confidential business or customer information. ## Goose AI Pricing: Is It Free? Goose is free and open-source software released under the Apache 2.0 licence. You can download and use the application without paying a Goose software subscription fee. However, the total cost depends on the AI model and external services you choose. Your open source AI agent+1 Pricing overview checked against the official project documentation. Model-provider charges and subscription terms can change. | Plan or component | Price | What you get | | ----------------- | ----- | ------------ | | Goose Desktop | Free | Desktop AI agent for supported operating systems | | Goose CLI | Free | Terminal-based agent for development and automation | | Open-source software | Free | Access to the project under the Apache 2.0 licence | | Local AI models | Potentially free | Run supported models locally; hardware and electricity still cost money | | Cloud [AI APIs](https://abcaitools.com/cracked/) | Varies by provider | Use supported cloud models, often with usage-based billing | | Paid AI subscriptions | Varies by provider | Use eligible subscriptions through supported integrations | | External services and extensions | Varies | Some services may require paid accounts, API access, or separate subscriptions | Is there a paid Goose Pro plan? The official project documentation presents Goose as free, open-source software. The pricing of connected AI models and third-party services should be checked separately rather than assuming that every feature or integration is free. For current model costs, visit the relevant provider's official pricing page. If you want to minimise expenses, start with a compatible local model or a provider's free tier, if available. ## How to Get Started With Goose AI Getting started is easier if you begin with a small task instead of immediately connecting multiple tools. Follow these steps: - Visit the official website. Open [Goose's official documentation](https://goose-docs.ai/?utm_source=abcaitools.com) and select the desktop or CLI installation option. - Install the application. Choose the version for Windows, macOS, or Linux. - Configure an AI model. Select a supported provider and follow its authentication instructions. You may need an API key or an eligible subscription. - Start a session. Give Goose a simple instruction, such as asking it to create a small HTML page in a test folder. - Enable extensions if needed. Add only the tools required for your task. - Review the output. Check the files, commands, and results before using them in important projects. The official quickstart guide provides more detailed instructions for installation, model configuration, and your first session. Your open source AI agent+1 A useful first test is to ask Goose to create a simple webpage in a new, empty folder. This lets you explore its capabilities without risking important files. ## Pros and Cons of Goose AI ### Pros - Free and open source: No separate Goose software subscription is required. - Flexible model choices: Connect to multiple AI providers and supported local models. - Works with real files: Can inspect and edit files and execute commands when permitted. - Useful MCP support: Connects to many external tools and data sources. - Reusable workflows: Recipes help automate repeated tasks. - Parallel work: Subagents can handle separate parts of a larger task. - Multiple interfaces: Desktop, terminal, and API options suit different users. - Security features: Permission controls and sandboxing help manage risks. ### Cons - Setup takes time: Configuring models, API keys, and extensions can be confusing for beginners. - Possible model costs: Cloud usage may require paid API credits or a subscription. - Hardware limitations: Local models may need substantial memory and processing power. - Not always accurate: The agent can make mistakes in code, research, or file operations. - Security requires attention: Extensions may access sensitive data or perform powerful actions. - Results depend on the model: Some models handle tool calls and complex tasks better than others. - Not a completely hands-off solution: Important work still needs human review. ## Who Should Use Goose AI? Goose is a good option for people who want more control over how they use AI. Its flexibility makes it useful for several types of users. - Developers: Build applications, edit code, run tests, and investigate software issues. - Technical teams: Create reusable workflows and automate repeated development tasks. - AI enthusiasts: Experiment with different models and open-source AI systems. - Privacy-conscious users: Run suitable models locally and keep compatible workflows on their computers. - Content creators: Organise research, process files, prepare drafts, and automate parts of their content workflow. - Businesses: Explore custom AI workflows that connect models with their existing tools and services. However, if you only need to ask questions, summarise text, or generate ideas, a standard hosted chatbot may be easier to use. Goose becomes more valuable when you want AI to interact with your files, software, and connected tools. ## Is Goose AI Worth Trying? Yes, Goose is worth trying if you want an AI agent that can do more than generate text. Its combination of local execution, support for multiple AI providers, MCP extensions, reusable Recipes, and parallel subagents makes it a flexible option for development and automation. Its biggest advantage is control. You can choose your model, configure your tools, and build workflows around your own needs instead of depending on one closed platform. The main drawback is the learning curve. You may need some technical knowledge to configure providers, install extensions, and manage permissions. Cloud models can also add costs, while local models depend on your computer's capabilities. Final thought: Goose is a strong choice for developers, technical users, and people interested in open-source [AI automation](https://abcaitools.com/cometapi/). If you want a simple chatbot, it may be more than you need. But if you want an AI agent that can work with files, run commands, connect to tools, and automate repeatable tasks, Goose is an excellent project to explore. ## Alternatives to Goose AI Here are five alternatives worth considering. Each offers some overlapping capabilities, but the available models, interfaces, and automation features differ. **1. [Antigravity](https://abcaitools.com/google-antigravity/)** An AI-powered development environment designed for agent-led coding and multi-step tasks. It can help developers work across code, terminal operations, and browser-based testing, depending on the available features. **2. OpenCode** An open-source coding agent for working with codebases, editing files, and running development tasks. It supports multiple AI providers and is a good option for users who want a flexible coding workflow. **3. Cline** An AI coding agent that can edit project files, execute terminal commands, and work through multi-step development tasks with approval controls. It is particularly useful for developers who prefer working inside their editor. **4. OpenAI Codex** An AI coding agent for implementing features, fixing bugs, and running development tasks. Its cloud-based workflows can help with parallel coding work and reviewing changes before they are merged. **5. Hermes Agent** An [autonomous AI agent](https://abcaitools.com/companyclaw/) designed to run on your own infrastructure and build reusable skills from completed tasks. It is worth exploring if you want persistent workflows and an agent that can improve how it handles repeated work.