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README.md

Mastra agents with memory sharing + Trigger.dev task orchestration example project:

ℹ️ Note: This is a Trigger.dev v4 project. If you are using v3 and want to upgrade, please refer to our v4 upgrade guide.

Enter a city and an activity, and get a clothing recommendation generated for you based on today's weather.

agent-output

By combining Mastra's persistent memory system and agent orchestration with Trigger.dev's durable task execution, retries and observability, you get production-ready AI workflows that survive failures, scale automatically, and maintain context across long-running operations.

Tech stack

  • Node.js runtime environment
  • Mastra for AI agent orchestration and memory management
  • PostgreSQL for persistent storage and memory sharing
  • Trigger.dev for task orchestration, batching, and observability
  • OpenAI GPT-4 for natural language processing
  • Open-Meteo API for weather data (no API key required)
  • Zod for schema validation and type safety

Featured patterns

Project Structure

src/
├── mastra/
│   ├── agents/
│   │   ├── weather-analyst.ts    # Weather data collection
│   │   ├── clothing-advisor.ts   # Clothing recommendations
│   ├── tools/
│   │   └── weather-tool.ts       # Enhanced weather API tool
│   ├── schemas/
│   │   └── weather-data.ts       # Weather schema
│   └── index.ts                  # Mastra configuration
├── trigger/
│   └── weather-task.ts           # Trigger.dev tasks

Relevant code

Storage Architecture

This project uses a centralized PostgreSQL storage approach where a single database connection is shared across all Mastra agents. This prevents duplicate database connections and ensures efficient memory sharing between the weather analyst and clothing advisor agents.

Storage Configuration

The storage is configured once in the main Mastra instance (src/mastra/index.ts) and automatically inherited by all agent Memory instances. This eliminates the "duplicate database object" warning that can occur with multiple PostgreSQL connections.

The PostgreSQL storage works seamlessly in both local development and serverless environments with any PostgreSQL provider, such as:

Running the project

  1. After cloning the repo, run npm install to install the dependencies.
  2. Set up your environment variables (see .env.example)
  3. If you haven't already, sign up for a free Trigger.dev account here and create a new project.
  4. Copy the project ref from the Trigger.dev dashboard and add it to the trigger.config.ts file.
  5. In your terminal, run the Trigger.dev dev CLI command with npx trigger.dev@v4-beta dev.

Now you should be able to visit your Trigger.dev dashboard and test any of the agent tasks with the example payloads provided in each task file.

Testing

Example payload

{
  "city": "New York",
  "activity": "walking"
}

Learn More

To learn more about the technologies used in this project, check out the following resources: