Coding Agents on Databricks Apps

Run Claude Code, Codex, Gemini CLI, and OpenCode in your browser — zero setup, wired to your Databricks workspace.

---

What's Inside

🟠 Claude Code — Anthropic's coding agent with 39 Databricks skills + 2 MCP servers

🟣 Codex — OpenAI's coding agent, pre-configured for Databricks

🔵 Gemini CLI — Google's coding agent with shared skills

🟢 OpenCode — Open-source agent with multi-provider support

Every agent starts pre-wired to your Databricks AI Gateway — models, auth tokens, and base URLs are all configured at boot. No API keys to manage.

---

Terminal Features

🎨 8 Themes	Dracula, Nord, Solarized, Monokai, GitHub Dark, and more
✂️ Split Panes	Run two sessions side by side with a draggable divider
🔍 Search	Find anything in your terminal history (Ctrl+Shift+F)
🎤 Voice Input	Dictate commands with your mic (Option+V)
⌨️ Customizable	Fonts, font sizes, themes — all persisted across sessions
🐍 Loading Screen	Play snake while 6 setup steps run in parallel
🔄 Workspace Sync	Every git commit auto-syncs to /Workspace/Users/{you}/projects/
✏️ Micro Editor	Modern terminal editor, pre-installed
⚙️ Databricks CLI	Pre-configured with your PAT, ready to go

---

Quick Start

Deploy to Databricks Apps

1. Go to Databricks → Apps → Create App
2. Choose Custom App and connect this Git repo:

   https://github.com/datasciencemonkey/coding-agents-in-databricks.git
   

3. Add your PAT as the DATABRICKS_TOKEN secret in App Resources
4. Deploy

That's it. Open the app URL and start coding.

→ Full deployment guide — environment variables, gateway config, and advanced options.

Run locally

git clone https://github.com/datasciencemonkey/coding-agents-in-databricks.git
cd coding-agents-in-databricks
uv run python app.py

Open http://localhost:8000 — type claude, codex, gemini, or opencode to start coding.

---

Why This Exists

On Jan 26, 2026, Andrej Karpathy made this viral tweet about the future of coding. Boris Cherny, the creator of Claude Code, responded:

This app template opens that vision up for every Databricks user — no IDE setup, no local installs. Just open the browser and start coding with AI.

---

🧠 All 39 Skills

Databricks Skills (25) — ai-dev-kit

Category	Skills
AI & Agents	agent-bricks, genie, mlflow-eval, model-serving
Analytics	aibi-dashboards, unity-catalog, metric-views
Data Engineering	declarative-pipelines, jobs, structured-streaming, synthetic-data, zerobus-ingest
Development	asset-bundles, app-apx, app-python, python-sdk, config, spark-python-data-source
Storage	lakebase-autoscale, lakebase-provisioned, vector-search
Reference	docs, dbsql, pdf-generation
Meta	refresh-databricks-skills

Superpowers Skills (14) — obra/superpowers

Category	Skills
Build	brainstorming, writing-plans, executing-plans
Code	test-driven-dev, subagent-driven-dev
Debug	systematic-debugging, verification
Review	requesting-review, receiving-review
Ship	finishing-branch, git-worktrees
Meta	dispatching-agents, writing-skills, using-superpowers

🔌 2 MCP Servers

Server	What it does
DeepWiki	Ask questions about any GitHub repo — gets AI-powered answers from the codebase
Exa	Web search and code context retrieval for up-to-date information

🏗️ Architecture

┌─────────────────────┐     HTTP      ┌─────────────────────┐
│   Browser Client    │◄────────────►│   Gunicorn + Flask   │
│   (xterm.js)        │   Polling     │   (PTY Manager)     │
└─────────────────────┘               └─────────────────────┘
         │                                     │
         │ on first load                       │ on startup
         ▼                                     ▼
┌─────────────────────┐               ┌─────────────────────┐
│   Loading Screen    │               │   Background Setup  │
│   (snake game)      │               │   (6 parallel steps)│
└─────────────────────┘               └─────────────────────┘
                                               │
                                               ▼
                                      ┌─────────────────────┐
                                      │   Shell Process     │
                                      │   (/bin/bash)       │
                                      └─────────────────────┘

Startup Flow

1. Gunicorn starts, calls initialize_app() via post_worker_init hook
2. App immediately serves the loading screen (snake game)
3. Background thread runs setup: git config, micro editor, Claude CLI, Codex CLI, OpenCode, Gemini CLI, Databricks CLI
4. /api/setup-status endpoint reports progress to the loading screen
5. Once complete, the loading screen transitions to the terminal UI

API Endpoints

Endpoint	Method	Description
/	GET	Loading screen (during setup) or terminal UI
/health	GET	Health check with session count and setup status
/api/setup-status	GET	Setup progress for loading screen
/api/session	POST	Create new terminal session
/api/input	POST	Send input to terminal
/api/output	POST	Poll for terminal output
/api/resize	POST	Resize terminal dimensions
/api/session/close	POST	Close terminal session

⚙️ Configuration

Environment Variables

Variable	Required	Description
DATABRICKS_TOKEN	Yes	Your Personal Access Token (secret)
HOME	Yes	Set to /app/python/source_code in app.yaml
ANTHROPIC_MODEL	No	Claude model name (default: databricks-claude-opus-4-6)
CODEX_MODEL	No	Codex model name (default: databricks-gpt-5-2)
GEMINI_MODEL	No	Gemini model name (default: databricks-gemini-3-1-pro)
DATABRICKS_GATEWAY_HOST	No	AI Gateway URL (recommended)

Security Model

Single-user app — each user deploys their own instance with their own PAT. Only the token owner can access the terminal. Everyone else sees 403.

Gunicorn

Production uses workers=1 (PTY state is process-local), threads=8 (concurrent polling), gthread worker class.

📁 Project Structure

coding-agents-in-databricks/
├── app.py                   # Flask backend + PTY management + setup orchestration
├── app.yaml.template        # Databricks Apps deployment config template
├── gunicorn.conf.py         # Gunicorn production server config
├── requirements.txt         # Python dependencies
├── setup_claude.py          # Claude Code CLI + MCP configuration
├── setup_codex.py           # Codex CLI configuration
├── setup_gemini.py          # Gemini CLI configuration
├── setup_opencode.py        # OpenCode configuration
├── setup_databricks.py      # Databricks CLI configuration
├── sync_to_workspace.py     # Post-commit hook: sync to Workspace
├── install_micro.sh         # Micro editor installer
├── static/
│   ├── index.html           # Terminal UI (xterm.js + split panes)
│   ├── loading.html         # Loading screen with snake game
│   └── lib/                 # xterm.js library files
├── .claude/
│   └── skills/              # 39 pre-installed skills
└── docs/
    ├── deployment.md        # Full Databricks Apps deployment guide
    └── plans/               # Design documentation

---

Technologies

Flask · Gunicorn · xterm.js · Python PTY · Databricks SDK · Databricks AI Gateway