Building Smart Cloud Workflows: My Experience Integrating Tiger Cloud and MCP with Google Antigravity

During this Global Hack Week, I embarked on a journey to explore advanced cloud infrastructure, repository management best practices, and AI-driven workflow integrations. One of the most exciting parts of this learning curve was connecting Tiger Cloud with my AI agent using the Tiger CLI and Model Context Protocol (MCP).

Here is a breakdown of what I built, how it works, and the technical hurdles I overcame along the way.

1. Establishing Repository Best Practices

Before diving into cloud automation, I focused on foundational software engineering standards for project repositories (such as the Mergington High School extracurricular project). To ensure clean collaboration and security, I implemented:

• CONTRIBUTING.md to guide future contributors on contribution workflows.

• CODEOWNERS to automate review assignments.

• SECURITY.md to define vulnerability reporting policies.

• Custom pull request templates to keep feature submissions standardized.

2. Setting Up Tiger Cloud and MCP Integration

Moving into cloud infrastructure, the goal was to give my AI assistant direct, natural language access to cloud resources via the Model Context Protocol (MCP).

Step-by-Step Implementation:

1._ Authentication:_ Authenticated the local environment securely using the Tiger CLI:

tiger auth login

And configured write protections for production services to safeguard critical environments.

2. Installing the MCP Server:
Ran the interactive installation command to wire the Tiger MCP binary directly into my development environment:

tiger mcp install

This automatically generated the required configuration file at C:\Users\Admin.gemini\antigravity\mcp_config_json for Google Antigravity.

3. Interacting via Natural Language:
Once configured and restarted, the AI assistant gained the capability to manage cloud resources seamlessly. Instead of manual CLI navigation, I could prompt commands like:

- "List my Tiger Cloud services"
- "Help me create a new database schema for my application"

Key Takeaways

Integrating Tiger MCP into an AI agent environment bridges the gap between conversational AI and heavy backend infrastructure management. It drastically reduces context-switching and allows developers to query data, inspect tables, and manage deployments using plain language.

Happy coding, and see you at the next hackathon! #mlhacks