
Open-source AI coding agent for terminal, desktop, and IDEs—plans changes, edits code, and can run tasks in GitHub via comments.
OpenCode is an open-source AI coding agent designed to help developers plan, implement, and refactor code from a terminal-first workflow, with options to use it as a desktop app or IDE extension. It can connect to multiple model providers (or use included free models), apply changes across a codebase, and support common developer flows like asking questions, adding features, making edits, and undoing changes. OpenCode also integrates with GitHub workflows: you can mention a command in issues or pull requests to have it execute tasks inside a GitHub Actions runner.
Product overview
OpenCode is an open-source coding agent and agent harness available in the terminal, desktop apps, IDEs, and GitHub Actions. It can inspect and edit repositories, run commands, delegate searches, use configurable tools, and connect to more than 75 hosted or local model providers.
Information as of August 18, 2026
Built-in build and plan agents can be extended with custom primary agents and subagents, distinct prompts, models, tool access, and permission policies.[2]
OpenCode supports more than 75 providers, custom OpenAI-compatible endpoints, and local models, while optional Zen supplies a curated pay-as-you-go model set.[3], [5]
GitHub Actions can trigger OpenCode from issue or review comments, schedules, pull requests, or manual workflows to investigate, implement changes, review code, and open pull requests.[4]
The MIT-licensed OpenCode client is free. Users pay their chosen model provider or run local models. Optional OpenCode Zen starts by adding a $20 pay-as-you-go balance plus card processing and charges provider prices per request with no markup.[1], [5]
Platforms: Terminal UI, macOS desktop, Windows desktop, Linux desktop, IDE extension, GitHub Actions[1], [3], [4]
Access: Local binary, Docker container, GitHub-hosted or self-hosted Actions runner, Local or hosted model endpoints[1], [3], [4]
Two independent hands-on reviews consistently highlight model-provider choice, open-source control, and native plan-versus-build modes. They also emphasize that results and cost depend on the selected model and that terminal-first operation remains a deliberate tradeoff.[6], [7]
74/100
Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.
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