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Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
npx claudepluginhub anthropics/claude-plugins-official --plugin dominodatalabInitialize a new Domino-ready web application with Vite+React, Streamlit, Dash, or Flask. Configures proxy-compatible settings and app.sh.
Debug Domino proxy and routing issues for web applications. Analyzes vite.config.js, package.json, and app.sh for misconfigurations.
Set up MLflow experiment tracking for traditional ML. Configures unique experiment names and auto-logging.
Set up GenAI tracing for an agent or LLM application. Adds Domino SDK imports, @add_tracing decorators, and DominoRun context.
Specialized agent for setting up new Domino projects, environments, and configurations. Use PROACTIVELY when starting a new project, configuring experiment tracking, setting up GenAI tracing, or initializing project structure.
Specialized agent for deploying applications, models, and endpoints to Domino. Use PROACTIVELY when deploying React/Streamlit/Dash apps, publishing model APIs, or configuring deployments.
Specialized agent for debugging Domino issues including app deployment problems, job failures, environment build errors, and connectivity issues. Use PROACTIVELY when troubleshooting errors or unexpected behavior in Domino.
Access external LLM providers through Domino AI Gateway - a secure proxy with centralized API key management, usage monitoring, and compliance. Supports OpenAI, AWS Bedrock, Azure OpenAI, Anthropic, and more. Use when calling LLMs from Domino, configuring AI Gateway endpoints, or monitoring LLM usage and costs.
Deploy web applications to Domino Data Lab with expertise in React apps (Vite) behind Domino's reverse proxy. Covers app.sh configuration, port configuration, base path handling for SPAs, CI/CD with GitHub Actions, and proxy troubleshooting. Use when deploying apps to Domino, setting up CI/CD pipelines, fixing broken routing, or configuring JavaScript frameworks for Domino's proxy.
Connect Domino workloads to external data sources including AWS S3 (via Mountpoint CSI driver), credential propagation with AWS IRSA and Azure Entra ID, and External Data Volumes. Use when configuring S3 access, setting up credential propagation, or connecting to cloud data sources from Domino.
Work with Domino Datasets - high-performance, versioned filesystem storage. Covers dataset creation, snapshots for versioning, sharing across projects, mounting paths (/domino/datasets/), and performance optimization. Use when managing data storage, creating reproducible data versions, or sharing data between projects.
Work with distributed computing frameworks in Domino including Apache Spark, Ray, and Dask clusters. Covers cluster configuration, on-demand clusters, choosing between frameworks, PySpark usage, and scaling workloads. Use when processing large datasets, parallel ML training, or running distributed compute jobs.
Requires secrets
Needs API keys or credentials to function
Uses power tools
Uses Bash, Write, or Edit tools
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Deploy ML models to production
Databricks development toolkit with skills for data engineering, ML, and AI agents plus MCP tools for direct Databricks operations
Automate ML workflows with Airflow, Kubeflow, MLflow. Use for reproducible pipelines, retraining schedules, MLOps, or encountering task failures, dependency errors, experiment tracking issues.
Agents for data engineering, machine learning, and AI development
High-intelligence Claude Code copilot with deep code reasoning, evidence-driven planning, orchestration-first execution, model routing, context budgeting, CI/CD integration, enterprise security, plugin development, prompt engineering, performance profiling, agent teams, channels (event-driven autonomy with CI webhook, mobile approval relay, Discord bridge, and fakechat dev profile), interactive tutorials, LSP integration, security-hardened hook script library, MCP Prompts coverage, common workflow packs, runtime selection guide, computer-use patterns, checkpointing, scheduled-task blueprints, repo bootstrap scanner, hook policy engine (8 installable packs), layered memory deployment, role-based subagent packs (implementer, debugger, migration-lead, dependency-auditor, release-coordinator), 5 agent-team topology kits, autonomy operating mode (4 profiles + 3 gates), and a queryable 15-tool MCP documentation server with autonomy advisor.
Data engineering, ML, and AI specialists - data pipelines, machine learning, LLM architecture
A comprehensive Claude Code plugin providing full coverage of the Domino Data Lab platform for AI-assisted development.
This plugin enables Claude Code to help you with all aspects of Domino Data Lab, including:
claude --version to check)uv package manager (install guide) — required for the bundled Domino MCP serverThis approach registers the plugin through Claude Code's native marketplace system so it persists across sessions.
Step 1: Clone the repository and create a marketplace wrapper
# Clone the plugin
git clone https://github.com/dominodatalab/domino-claude-plugin.git
# Create the marketplace directory structure
mkdir -p ~/.claude/marketplaces/domino/.claude-plugin
mkdir -p ~/.claude/marketplaces/domino/plugins
# Move the plugin into the marketplace
mv domino-claude-plugin ~/.claude/marketplaces/domino/plugins/domino-claude-plugin
Step 2: Create the marketplace manifest
cat > ~/.claude/marketplaces/domino/.claude-plugin/marketplace.json << 'EOF'
{
"name": "domino-marketplace",
"owner": {
"name": "Domino Data Lab",
"email": "support@dominodatalab.com"
},
"plugins": [
{
"name": "domino-claude-plugin",
"description": "Domino Data Lab plugin for Claude Code - workspaces, jobs, environments, datasets, apps, models, and more",
"version": "1.0.0",
"source": "./plugins/domino-claude-plugin",
"category": "development"
}
]
}
EOF
Step 3: Register the marketplace and install the plugin
Launch Claude Code and run:
/plugin marketplace add /home/<your-username>/.claude/marketplaces/domino
/plugin install domino-claude-plugin@domino-marketplace
Note: Replace
<your-username>with your actual username, or use the full absolute path (e.g.,/home/ubuntu/.claude/marketplaces/domino). The~shorthand may not expand correctly.
Step 4: Restart Claude Code
/exit
claude
The plugin should appear in your loaded plugins on startup. Verify with:
/plugin
Navigate to the Installed tab to confirm domino-claude-plugin is listed.
Use the --plugin-dir flag to load the plugin directly. This is ideal for development, testing, or quick evaluation.
# Clone the plugin
git clone https://github.com/dominodatalab/domino-claude-plugin.git
# Ensure the plugin manifest exists
mkdir -p domino-claude-plugin/.claude-plugin
cat > domino-claude-plugin/.claude-plugin/plugin.json << 'EOF'
{
"name": "domino-claude-plugin",
"description": "Domino Data Lab plugin for Claude Code",
"version": "1.0.0"
}
EOF
# Run Claude Code with the plugin
claude --plugin-dir ./domino-claude-plugin
To make this persistent without the marketplace approach, add a shell alias:
echo 'alias claude="claude --plugin-dir /path/to/domino-claude-plugin"' >> ~/.bashrc
source ~/.bashrc
For teams sharing a project, add the marketplace to your project's .claude/settings.json:
{
"extraKnownMarketplaces": {
"domino-marketplace": {
"source": {
"source": "directory",
"path": "/path/to/domino-marketplace"
}
}
},
"enabledPlugins": {
"domino-claude-plugin@domino-marketplace": true
}
}
When team members trust the repository folder, Claude Code will prompt them to install the marketplace and plugin automatically.
After installation, test that the plugin is working:
Check slash commands are available:
/domino-app-init
Test skill auto-invocation by asking a Domino-related question:
Help me deploy a Streamlit app to Domino
Claude should automatically invoke the domino-app-deployment skill.
Check the plugin is listed:
/plugin
Navigate to the Installed tab.