
Understand why the model context protocol (mcp) connects your open code agent to external tools like GitHub and Jira, using a json mcp configuration file.
Connect your OpenCode agent to GitHub via the MCP server, configure open code.json, and fetch and convert updated Amazon sales data to CSV for storage.
Stop paying for AI coding subscriptions. Start running autonomous agents for free.
OpenCode is the open-source AI coding agent built for the terminal — provider-agnostic, MIT-licensed, and able to run entirely on free AI models. This crash course takes you from installation to a packaged, shareable agent toolkit in under four hours.
This is not a course about typing prompts and hoping for the best. You will build a complete, reproducible automation system: custom slash commands, a project-aware AGENTS md file, MCP connections to GitHub and your database, two production Skills, a custom sub-agent, and your own distributable OpenCode plugin.
What you will build
Every hands-on lesson runs against one real case study — a messy retail sales dataset with duplicate orders, inconsistent date formats, currency-formatted text, and missing regions. You will clean it, analyse it, and dashboard it using agents you build yourself.
A Data Cleaning Skill that handles real-world data defects through rules you write
A Dashboard Creation Skill that turns clean data into visual reporting
A Code Reviewer sub-agent that audits your work automatically
A shareable plugin bundling your skill, agent, and command into one installable package
What you will learn
How the OpenCode agentic loop works internally: read, reason, act, verify
Free setup using Zen models, plus paid configuration in three minutes if you want it
Plan mode vs Build mode, and why separating reasoning from execution reduces errors
Context windows, auto-compaction, and how to keep agents on track in long sessions
Writing and testing an AGENTS md file so your agent understands your project
MCP from first principles: GitHub, database servers, Context7, and the allow/ask/deny trust model
Skills architecture: YAML front-matter and Markdown body, plus installing from the marketplace
Sub-agents vs Skills, and exactly when to reach for each
Packaging and distributing your work as an OpenCode plugin
Who this course is for
Developers, data analysts, and engineers who want agentic coding without a paid subscription. Anyone curious about terminal-based AI agents who wants a practical workflow rather than a feature tour. Students, freelancers, and indie builders automating repetitive coding and data work.