nocodb-to-trigger

name	nocodb-to-trigger
description	This skill should be used when the user wants to "trigger background task from NocoDB", "connect NocoDB to Trigger.dev", "process NocoDB data with Trigger.dev", "run background job on NocoDB change", or needs to integrate NocoDB data events with Trigger.dev background tasks.

NocoDB to Trigger.dev Integration

Patterns for triggering Trigger.dev background tasks from NocoDB data events. Use for long-running operations, AI processing, and durable execution that would timeout in n8n.

When to Use Trigger.dev vs n8n

Use Case	Service	Reason
Short workflow (<30s)	n8n	Visual workflow, quick execution
Long-running job (>30s)	Trigger.dev	Durable execution, retries
AI/LLM processing	Trigger.dev	Token streaming, long waits
Multi-step orchestration	Trigger.dev	Checkpointing, resumability
Simple webhook relay	n8n	Low overhead, visual
File processing	Trigger.dev	Large memory, long timeouts

Integration Patterns

Pattern 1: NocoDB Webhook → n8n → Trigger.dev Task

Chain through n8n as a lightweight dispatcher.

[NocoDB Webhook] → [n8n: Parse + Validate] → [n8n: Trigger Task via API] → [Trigger.dev: Process]

n8n Code node to trigger a task:

const taskId = 'your-task-id';
const payload = $json.body.data.rows[0];

const response = await fetch(`${process.env.TRIGGER_API_URL}/api/v1/tasks/${taskId}/trigger`, {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.TRIGGER_SECRET_KEY}`,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({ payload })
});

return { json: await response.json() };

Pattern 2: Direct Trigger via MCP

Trigger a task directly using the Trigger.dev MCP tools.

Tool: mcp__trigger-dev__trigger_task
Input: {
  "taskId": "process-nocodb-record",
  "payload": {
    "recordId": 123,
    "tableId": "tbl_xxx",
    "action": "process"
  }
}

Pattern 3: Batch Processing

Process multiple NocoDB records as background tasks.

Trigger.dev task structure:

import { task } from "@trigger.dev/sdk/v3";

export const processRecords = task({
  id: "process-nocodb-records",
  retry: { maxAttempts: 3 },
  run: async (payload: { tableId: string; filter: string }) => {
    // 1. Query records from NocoDB
    // 2. Process each record
    // 3. Update status back in NocoDB
    // 4. Return summary
  },
});

Pattern 4: AI Processing Pipeline

Use Trigger.dev for AI-powered processing of NocoDB data.

import { task } from "@trigger.dev/sdk/v3";

export const aiProcessRecord = task({
  id: "ai-process-record",
  machine: { preset: "medium-1x" },
  retry: { maxAttempts: 2 },
  run: async (payload: { recordId: number; tableId: string }) => {
    // 1. Fetch record from NocoDB
    // 2. Send to LLM for processing
    // 3. Store result back in NocoDB
    // 4. Update record status
  },
});

Monitoring Task Runs

Check task status via MCP:

Tool: mcp__trigger-dev__get_run_details
Input: { "runId": "run_xxx" }

List recent runs:

Tool: mcp__trigger-dev__list_runs
Input: { "limit": 10 }

Error Handling

1. Trigger.dev retries — configure retry.maxAttempts on the task
2. Status tracking — update a processing_status field in NocoDB (pending → processing → completed / failed)
3. Error logging — write errors to a NocoDB task_errors table with run ID, error message, and timestamp
4. Alerting — chain a notification task on failure (Slack, email via n8n)

Best Practices

• Use descriptive task IDs: process-order-payment, generate-ai-summary
• Include the NocoDB record ID and table ID in every task payload
• Update NocoDB record status before and after processing
• Use Trigger.dev queues for rate-limited operations
• Set appropriate machine presets for CPU/memory-intensive tasks
• Use idempotencyKey based on record ID to prevent duplicate processing