Opencode Python Wrapper

Problem

When driving OpenCode's AI coding agents directly from Python, scripts often need to handle request assembly, agent mode selection, context passing, and result handling. The Build, Plan, and General agents can easily end up scattered across scripts, services, or automation tasks, with no consistent entry point. For developers integrating coding agents into local tooling, batch workflows, or GitHub automation, the real issue is not whether the agent can be called, but whether the call path feels natural from Python.

How It Works

opencode-wrap wraps OpenCode's agent capabilities in a Python-oriented interface:

• Agent mode separation: Maps to Build, Plan, and General agent scenarios, making it easier to choose the right entry point by task type.
• MCP support: Useful for bringing external tools, documents, or context into the agent workflow instead of hardcoding all capabilities into the script.
• Workflow integration: Fits into Python services, scheduled jobs, CI pipelines, or local automation scripts, reducing manual handling of lower-level parameters.
• Clear wrapper boundary: It behaves more like a Python invocation layer for OpenCode, not a replacement for a full IDE, editor plugin, or complex platform.

Scope

This skill is best suited for development orchestration and automation integration. If the environment lacks an available OpenCode agent backend, is missing MCP configuration, or the goal is only a one-off command-line run, the value is limited. In practice, pay attention to agent mode, MCP tool sources, and the Python runtime environment.