Local AI Coding Setup: Ollama + OpenCode on macOS Terminal

Local AI Coding Setup: Ollama + OpenCode (macOS Terminal)

Want a fully local AI coding agent running in your terminal with zero cloud dependencies? This guide walks you through setting up Ollama (local LLM runner) and OpenCode (open-source AI coding agent) on macOS with Apple Silicon. The result: agentic coding capabilities, tool use, multi-model support, all running on your machine.

MLX-CODE vs Ollama + OpenCode

If you read our MLX-CODE article, you might wonder how this setup compares. Here's a quick breakdown:

Both approaches are valid. MLX-CODE is lighter and more self-contained; Ollama + OpenCode is more feature-rich for agentic coding workflows.

System Requirements

Step 1. Install Ollama

Ollama is a local LLM runner that manages model downloads, serves an OpenAI-compatible API, and handles GPU acceleration automatically.

# Install via Homebrew
brew install ollama

# Verify installation
ollama --version

# Start the server (keep running in a terminal tab)
ollama serve

Keep ollama serve running, OpenCode connects to it via the local API.

Step 2. Download Coding Models

Pull one or more models optimized for code generation:

# Recommended, best quality/speed balance
ollama pull qwen2.5-coder:7b

# Alternatives
ollama pull deepseek-coder:6.7b
ollama pull codellama:7b

# List installed models
ollama list

# Remove a model
ollama rm model-name

Step 3. Verify the Ollama API

Ollama exposes two endpoints. OpenCode uses the OpenAI-compatible one:

# Check Ollama native API
curl http://localhost:11434/api/tags

# Check OpenAI-compatible endpoint (used by OpenCode)
curl http://localhost:11434/v1/models

Step 4. Configure Model Context Window

Ollama defaults to a 4K context window, which is too small for agentic coding. You need at least 16K:

# Create a 16K context variant
ollama run qwen2.5-coder:7b
/set parameter num_ctx 16384
/save qwen2.5-coder:7b-16k
/bye

# For even better results (if you have 16GB+ RAM)
ollama run qwen2.5-coder:7b
/set parameter num_ctx 32768
/save qwen2.5-coder:7b-32k
/bye

This creates new model variants with the increased context. Use these names in your OpenCode config.

Step 5. Test the Model

# Interactive chat to verify it works
ollama run qwen2.5-coder:7b-16k

# Try a coding prompt
> write a debounce function in typescript

# Exit
/bye

Step 6. Install OpenCode

OpenCode is an open-source AI coding agent with a terminal TUI, plan/build modes, tool use, and undo/redo. Install globally via npm:

# Install globally
npm install -g opencode-ai

# Verify
opencode --help

Other install methods: Homebrew (brew install opencode), Bun, pnpm, Yarn, or Docker.

Step 7. Connect OpenCode to Ollama

Create the configuration file to connect OpenCode to your local Ollama instance:

# Create config directory
mkdir -p ~/.config/opencode

# Create config file
nano ~/.config/opencode/opencode.json

Paste this configuration:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "ollama": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Ollama",
      "options": {
        "baseURL": "http://localhost:11434/v1"
      },
      "models": {
        "qwen2.5-coder:7b-16k": {
          "tools": true
        }
      }
    }
  },
  "model": "ollama/qwen2.5-coder:7b-16k"
}

Step 8. Use OpenCode

Navigate to any project and launch:

cd /path/to/your/project
opencode .

OpenCode Key Features

• Plan Mode

  Press Tab to toggle. Generates implementation strategies without modifying code. Great for reasoning through complex tasks first.

• Build Mode

  The default mode. OpenCode reads, writes, and modifies files in your project with tool use capabilities.

• Undo / Redo

  Use /undo and /redo to revert or restore changes. Safe experimentation.

• File References

  Press @ to fuzzy-search and attach project files to your prompt. Context-aware conversations.

• AGENTS.md

  Run /init to generate an AGENTS.md file. OpenCode learns your project patterns and conventions.

• Share Conversations

  Use /share to create a shareable link of your conversation for team collaboration.

Multi-Model Configuration

Add multiple models and switch between them with Ctrl+A:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "ollama": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Ollama",
      "options": {
        "baseURL": "http://localhost:11434/v1"
      },
      "models": {
        "qwen2.5-coder:7b-16k": {
          "tools": true
        },
        "deepseek-coder:6.7b": {
          "tools": true
        },
        "codellama:7b": {
          "tools": true
        }
      }
    }
  },
  "model": "ollama/qwen2.5-coder:7b-16k",
  "small_model": "ollama/codellama:7b"
}

The small_model is used for lightweight tasks like generating titles or summaries.

Recommended Models by Task

Remember to create 16K+ context variants for each model you use with agentic workflows.

Troubleshooting

Quick Reference Commands

# Ollama
ollama serve                          # Start server
ollama list                           # List models
ollama pull qwen2.5-coder:7b          # Download model
ollama rm model-name                  # Remove model
curl http://localhost:11434/api/tags   # Check status
curl http://localhost:11434/v1/models  # OpenAI-compatible check

# OpenCode
opencode .                            # Launch in current project
/init                                 # Generate AGENTS.md
/undo                                 # Undo last change
/redo                                 # Redo last change
/share                                # Share conversation
/help                                 # List all commands
Tab                                   # Toggle plan/build mode
Ctrl+A                                # Switch models
@                                     # Fuzzy-search project files

Conclusion

With Ollama and OpenCode you get a fully local, privacy-first AI coding agent with agentic capabilities that rival cloud-based tools. No API keys, no subscriptions, no data leaving your machine.

If you're already using MLX-CODE for quick local inference, consider adding Ollama + OpenCode to your toolkit for more complex agentic workflows. Both tools complement each other: MLX-CODE for lightweight, GPU-native inference and OpenCode for full-featured coding agent capabilities.

Resources

• OpenCode Documentation

  Official docs for installation, configuration, providers, and commands.

• Ollama Documentation

  Model library, API reference, and advanced configuration.

• Ollama x OpenCode Guide

  Community guide for connecting Ollama with OpenCode.

• AI Terminal Coding (GitHub)

  Full setup instructions and configuration files for the Ollama + OpenCode workflow covered in this article.

• MLX-Terminal-Code (GitHub)

  Source code and setup for MLX-CODE, the local AI coding assistant covered in our previous article.

• MLX-CODE on CodeHelper

  Our previous article on local AI coding with Apple's MLX framework.