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Editorial snapshot from September 2026. Prices, models and interface labels may change; this is a practical guide, not a live product feed.

An open-source agent that connects model providers, MCP tools and repeatable recipes.

Coding agent · Agentic AI Foundation / Block · macOS · Linux

Suitable workflows

Developers automating local workflows with extensible tools and provider choice.

Limitations and billing

The client is free; external model providers and connected services may charge separately.

Capabilities we verified

Agent workflow · CLI surface · MCP · Bring your own key

This is an evidence-based shortlist, not an exhaustive feature inventory. Omitted capabilities have not been checked for this record.

Pricing & usage

See official pricing

Free CLI; model-provider or optional service charges. The cost of metered usage or an external agent can be separate from the subscription.

Models & access

Choose a supported model provider or an ACP agent as the execution provider.

Install and start the CLI

Use the official CLI installer and configure a supported provider before starting a session.

curl -fsSL https://github.com/aaif-goose/goose/releases/download/stable/download_cli.sh | bash

Open your project folder in a terminal, then run:

goose session

Account and authentication

Run goose configure to select your provider and its credentials.

Project configuration and tools

Extensions expose MCP tools; recipes capture repeatable workflows for later runs.

First task to try

Inspect a local project and connect only the tools needed for one bounded task.

Related CLI tools

All AI CLI tools →

OpenCode — An open-source coding agent with a terminal UI and configurable model providers.

Mistral Vibe — Mistral’s coding agent for terminal sessions, scripts and configurable local or hosted models.

Aider — Terminal pair programming with repository maps, editable file context and Git integration.

Project evaluation checklist

  1. Open a small, familiar project and confirm that your essential language tooling works.
  2. Give the agent one bounded change with an observable acceptance criterion.
  3. Review the diff, run the project’s checks and compare the result with your current workflow.
  4. Inspect usage after the task. Estimate a month of similar work, including any separate model or agent bill.

Related TRAE guides

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