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opencode

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Basic Information

OpenCode is a Go-based command line application that brings an AI coding assistant into the terminal. It provides an interactive terminal user interface for developers to interact with multiple large language model providers, manage conversational sessions, and invoke tools that can search, view, edit and patch code. The tool targets developer workflows by integrating Language Server Protocol features, persistent session storage in SQLite, external editor support, and the Model Context Protocol to extend capabilities with external tools. OpenCode can be used interactively in a TUI or in non-interactive mode for scripting, and it supports a variety of hosted and self-hosted model endpoints. The README documents installation paths, configuration locations, environment variables for provider keys, and a modular code layout for contributors.

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9253
App URL
https://github.com/opencode-ai/opencode
Github Repository
https://github.com/opencode-ai/opencode/blob/main/README.md

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App Details

Features
OpenCode bundles a set of developer-focused features: an interactive TUI built with Bubble Tea, multi-provider model support (OpenAI, Anthropic, Google Gemini, AWS Bedrock, Groq, Azure, OpenRouter and self-hosted endpoints), session management with persistent SQLite storage, and an integrated vim-like editor and external editor support. It exposes a toolset to the AI including file tools (glob, grep, ls, view, write, edit, patch, diagnostics) and runtime tools (bash, fetch, sourcegraph, agent). The project supports LSP integration for diagnostics, MCP for external tool discovery and secure permissioned execution, named arguments and custom commands stored as Markdown, auto-compaction of long conversations, keyboard shortcuts, non-interactive prompt mode with text or JSON output, and configurable shells and providers.
Use Cases
OpenCode helps developers by embedding AI assistance directly in the terminal so they can ask models to explain, debug, refactor or modify project code without leaving their workflow. The AI can search and inspect repository files, apply edits or patches, run shell commands, fetch external resources, and consult LSP diagnostics to suggest fixes. Session management and auto-compaction keep long interactions coherent while persistent storage preserves context. Custom commands and named arguments standardize common prompts and automation tasks. MCP support enables connecting external tools securely, and non-interactive mode allows scripting and CI usage. Multi-provider support and self-hosted endpoints give flexibility in choosing models for latency, cost, or privacy requirements.

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