====== Goose ======

**Goose** is an open-source, extensible AI coding agent developed by **Block** (formerly Square). With over **34,000 stars** on GitHub, Goose automates software development tasks — from building projects and debugging to orchestrating complex workflows — through natural language conversation. It is **MCP-native**, connecting to 1,700+ Model Context Protocol servers for extensible tool integration.(([[https://github.com/block/goose|GitHub Repository]]))(([[https://block.github.io/goose/docs/category/architecture-overview/|Architecture Documentation]]))(([[https://allthingsopen.org/articles/meet-goose-open-source-ai-agent|Meet Goose — All Things Open]]))

Goose goes beyond simple code generation by providing an executable infrastructure layer with composable YAML recipes, parallel subagents, and ambient terminal integration that fits seamlessly into existing developer workflows.

===== How It Works =====

Goose extends the standard LLM "text in, text out" paradigm with **tool integrations via MCP** (Model Context Protocol). The agent reasons through tasks using any connected LLM, then takes actions through MCP tools — file manipulation, testing, GitHub automation, and more. It supports GUI, CLI (REPL mode), terminal integration for ambient assistance, and CI/CD pipelines.

The **Recipes** system defines composable YAML workflows with typed parameters, sub-recipe calls, and explicit MCP pinning — making agent behaviors version-controlled, git-diffable, and team-shareable.

===== Key Features =====

  * **MCP-native** — First-class integration with 1,700+ MCP servers (GitHub, Jira, Google Drive, etc.)
  * **Recipes** — Composable YAML workflows with subagents and structured inputs
  * **Parallel subagents** — Isolated task execution; failures don't cascade
  * **Terminal integration** — Ambient mode in your existing shell, no context switching
  * **Model-agnostic** — Works with Claude, GPT-4o, local GGUF models via Docker Model Runner
  * **MCP-UI rendering** — Interactive widgets in GUI instead of raw text
  * **Fully configurable** — Disable any tool, even built-in ones

===== Installation and Usage =====

<code python>
# Goose can be installed and run via Docker Compose
# docker-compose.yml orchestrates Goose, Model Runner, and MCP Gateway

# Example Goose Recipe (YAML)
# recipes/analyze-pr.yaml
name: analyze-pr
description: Analyze a pull request for code quality
params:
  - name: pr_url
    type: string
    required: true
steps:
  - name: fetch_pr
    tool: github.get_pull_request
    input:
      url: "{{pr_url}}"
  - name: review
    prompt: |
      Review this PR for code quality, security issues,
      and adherence to best practices.
      PR Data: {{fetch_pr.output}}

# CLI Usage
# goose chat "Build a REST API with FastAPI for user management"
# goose run recipes/analyze-pr.yaml --pr_url https://github.com/org/repo/pull/42

# Terminal ambient mode
# goose next  (continues from current context)
</code>

===== Architecture =====

<code>
%%{init: {'theme': 'dark'}}%%
graph TB
    User([Developer]) -->|Natural Language| Interface[GUI / CLI / Terminal]
    Interface -->|Tasks| Agent[Goose Agent]
    Agent -->|Reasoning| LLM[LLM Provider]
    LLM -->|Claude / GPT / Local| Agent
    Agent -->|Tool Calls| Gateway[MCP Gateway]
    Gateway -->|Isolated Containers| GitHub[GitHub MCP]
    Gateway -->|Isolated Containers| Jira[Jira MCP]
    Gateway -->|Isolated Containers| GDrive[Google Drive MCP]
    Gateway -->|Isolated Containers| Custom[Custom MCPs]
    Agent -->|Execute| Recipes[Recipe Engine]
    Recipes -->|Spawn| SubA[Subagent A]
    Recipes -->|Spawn| SubB[Subagent B]
    SubA -->|Results| Recipes
    SubB -->|Results| Recipes
</code>

===== Docker Deployment =====

Goose is designed for Docker Compose deployment with three core services:(([[https://www.docker.com/blog/building-ai-agents-with-goose-and-docker/|Building AI Agents with Goose and Docker]]))

  * **Goose Agent** — Task execution and LLM reasoning
  * **Docker Model Runner** — Local LLM inference (OpenAI-compatible API), auto-pulls GGUF models
  * **MCP Gateway** — Aggregates and isolates MCP tools in containers with authenticated endpoints

===== See Also =====

  * [[open_interpreter|Open Interpreter — Natural Language Computer Interface]]
  * [[continue_dev|Continue.dev — Open-Source AI Code Assistant]]
  * [[chainlit|Chainlit — Conversational AI Framework]]

===== References =====