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goose

Goose is a general-purpose, native open-source AI agent available for macOS, Linux, and Windows, built on open standards like the Model Context Protocol (MCP) and Agent Client Protocol (ACP).

Free · macOS, Linux, Windows · API

What is goose?

goose is a general-purpose AI agent tool developed by Block (formerly Square) that enables engineers, developers, researchers, writers, and data analysts to automate tasks across various domains. It functions as an autonomous agent that can build, execute, test, and debug code independently, running directly on a user's machine with desktop, command-line interface (CLI), and API access. The agent emphasizes extensibility, supporting over 70 integrations through the Model Context Protocol (MCP) and Agent Client Protocol (ACP), and is an Apache 2.0 licensed project under the Agentic AI Foundation. It is designed for diverse workflows, including code generation, research, writing, automation, and data analysis, and is compatible with macOS, Linux, and Windows platforms.

Key Features of goose

Goose offers a comprehensive set of features designed for versatile AI agent functionality, emphasizing local operation and extensibility.

  • Native desktop application for macOS, Linux, and Windows.
  • Command-line interface (CLI) for scriptable automation.
  • API access for programmatic integration into existing systems.
  • Extensible architecture supporting over 70 integrations via the Model Context Protocol (MCP).
  • Compatibility with more than 15 LLM providers, including Anthropic, OpenAI, Google, Ollama, OpenRouter, Azure, and Bedrock.
  • Support for existing LLM subscriptions (e.g., Claude Code, ChatGPT, Gemini) through the Agent Client Protocol (ACP).
  • Security features, including prompt injection detection.
  • Built on open standards: Model Context Protocol (MCP) and Agent Client Protocol (ACP).

Who Should Use goose?

Goose is designed for a broad target audience requiring automation and AI assistance across various technical and creative domains.

  • Engineers and Developers: For automating engineering tasks like code migrations, refactoring, deployment, code reviews, and full-stack development.
  • Researchers and Data Analysts: To assist with research, data analysis, and workflow orchestration across multiple tools.
  • Writers: For content generation, summarization, and other writing-related automation.
  • QA Engineers: To automate tasks such as dependency updates, test execution, and code migration.
  • Users needing Task Automation: For general task automation across diverse domains, including onboarding to new projects or unfamiliar codebases.

How to Use goose

Goose can be utilized through its desktop application, command-line interface, or API, allowing users to automate tasks by defining objectives and leveraging its extensive integrations.

  1. Download and install the native desktop application for macOS, Linux, or Windows from goose-docs.ai.
  2. Configure your preferred LLM providers by adding API keys or linking existing subscriptions (e.g., OpenAI, Anthropic).
  3. Utilize the command-line interface (CLI) to initiate tasks, such as goose build project_description.
  4. Define specific objectives for code generation, research, writing, or automation tasks.
  5. Leverage the Model Context Protocol (MCP) extensions to integrate with databases, APIs, browsers, GitHub, and Google Drive.
  6. Monitor and debug agent execution, allowing Goose to self-correct errors and refine outputs.

goose Pricing & Plans

Goose is an open-source project released under the Apache 2.0 license, making it available for free. Users are responsible for any costs associated with third-party LLM API usage.

  • Goose: Free (Apache 2.0 licensed)

Pros

  • Native open-source AI agent available for macOS, Linux, and Windows.
  • Supports over 70 integrations through the Model Context Protocol (MCP).
  • Compatible with more than 15 LLM providers, including major services and local models.
  • Offers desktop, command-line interface (CLI), and API access for flexible usage.
  • Designed for diverse workflows, including code, research, writing, and automation.
  • Emphasizes data privacy by running locally on the user's machine.

Cons

  • Requires initial setup and configuration, which may be a hurdle for new users.
  • While robust, the command-line interface could benefit from a more interactive UI for some users.
  • Performance is dependent on local machine resources and chosen LLM provider.
  • Users are responsible for managing API keys and costs for third-party LLMs.

goose vs Competitors

Goose differentiates itself in the AI agent landscape through its local-first, open-source nature, and emphasis on broad workflow automation via open standards.

See every goose alternative, compared

goose

Free · macOS, Linux, Windows · API

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