This article provides a complete, practical walkthrough of the Manual Slack Automation Triggered n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Automating Uber Eats Expense Tracking with n8n, Gmail, and Slack
   
   Meta Description:  
   Streamline your food delivery expense management using n8n's automation workflow. Learn how to extract Uber Eats order data from Gmail and send it directly to Slack for easy budgeting and accounting.
   
   Keywords:  
   n8n automation, Uber Eats expense tracking, Gmail API, Slack API, expense automation, Gmail trigger, automate accounting, Slack integration, food delivery receipts, Moze accounting
   
   Third-party APIs Used:
   
   - Gmail API (OAuth2 authentication): For retrieving order confirmation emails from Uber Eats using keyword-based filters.
   - Slack API (OAuth2 authentication): For sending formatted messages (blocks) to designated Slack channels with order details and accounting links.
   
   Article:
   
   Automating Uber Eats Expense Tracking with n8n, Gmail, and Slack
   
   Managing personal finances often comes down to tracking small but frequent expenses—like food delivery. With the seamless integration of automation tools, you can completely eliminate manual entry and logging of Uber Eats orders. In this article, we introduce an n8n workflow named 外送記帳 ("Delivery Accounting") that transforms Gmail order confirmations into actionable, structured data posted directly to Slack—complete with smart links for automated logging into Moze, a popular Taiwanese personal finance app.
   
   What is n8n?
   
   n8n (short for “node-on-node”) is an open-source workflow automation tool that connects various services through nodes and allows businesses and individuals to automate tasks without writing complete programs. This low-code tool supports hundreds of integrations with third-party apps like Gmail, Slack, and databases, making it ideal for building efficient data workflows.
   
   Overview of the Workflow
   
   This specific workflow extracts relevant data like price, shop name, date, and time from Uber Eats confirmation emails, formats them into a Slack message, and includes a clickable link to log the transaction in Moze automatically.
   
   Here’s how the workflow is structured:
   
   1. Gmail Trigger – Looking for Uber Eats Emails
   
   The automation begins with a Gmail Trigger node, configured to poll Gmail every hour to search for emails with the subject:  
   "透過 Uber Eats 系統送出的訂單"  
   (Translated: "Order sent through the Uber Eats system").
   
   Using Gmail's search query filters, it ensures that only the relevant emails are processed.
   
   2. Manual Trigger – For Testing
   
   A Manual Trigger is also included to manually run the workflow during testing without waiting for the Gmail trigger.
   
   3. Retrieve Email Content
   
   Using the Get Emails from Gmail node, the workflow fetches matching emails. This node dives into every email found with the above subject and extracts its text content, which contains all the relevant order details.
   
   4. Loop Through Emails
   
   The SplitInBatches node iterates over each email returned. This ensures scalability if multiple orders are received in the same hour.
   
   5. Data Extraction
   
   Here’s where the magic happens. A Set node named "Extract Price, Shop, Date, Time" uses JavaScript regular expressions to extract specific pieces of information from the text body of each email:
   
   - Price: Extracted by matching amounts formatted with dollar signs (e.g., $280.00).
   - Shop Name: Found using the phrase “以下是您在 [Shop Name] 訂購…” (i.e., "Here is your order from [Shop Name]").
   - Date: Extracted and reformatted from "2024年6月5日" to "2024.6.5".
   - Time: Handles both 上午 (AM) and 下午 (PM) logic, converting time into 24-hour format for consistency.
   
   6. Post to Slack
   
   The final step is the Slack integration. It sends a message block to a specified Slack channel. This message includes:
   
   - Shop name
   - Order price
   - Order date
   - A clickable button that opens Moze with pre-filled data for quick entry, using the custom protocol moze3://.
   
   The Slack message is visually structured using Slack Blocks UI for clarity and better readability.
   
   Benefits of this Workflow
   
   - Time Savings: No more manually checking emails and updating budget apps or spreadsheets.
   - Accuracy: Extracted data is highly precise due to regex parsing.
   - Cross-Platform Integration: Connects Gmail, Slack, and Moze in a seamless way.
   - Convenient Logging: The Moze link within Slack makes accounting just a single click away.
   
   Use Case Scenarios
   
   This automation is ideal for:
   
   - Freelancers and remote workers who expense meals.
   - Budget-conscious users tracking personal food consumption.
   - Teams or roommates sharing a communal Slack channel for expenses.
   - Businesses reimbursing employees for client meal consumption.
   
   Conclusion
   
   In a world increasingly driven by digital interactions, small automations like this one can significantly improve productivity and reduce mental fatigue. Automating Uber Eats expense tracking with n8n, Gmail, and Slack brings real-world value by bridging the gap between raw data (order emails) and meaningful action (expense logging). It’s a simple yet powerful demonstration of how you can harness automation to make life just a bit easier, one receipt at a time.
   
   Future Improvements (Optional Enhancements)
   
   - Add a Google Sheets node to archive each transaction for long-term record-keeping.
   - Include sentiment analysis to detect restaurant satisfaction from order confirmation metadata.
   - Use OCR to grab data from attached receipts or PDFs if Uber Eats changes email formats.
   
   Whether you're a solo spender or part of a team, this n8n setup can help you take control of your meal expenses automatically—and effortlessly.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.