This article provides a complete, practical walkthrough of the Manual N8N 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:
   Supercharging Workflow Management: Query Your n8n Credentials with AI-Powered Search
   
   Meta Description:
   Learn how to build a no-code n8n workflow that lets you explore your workflow credentials using an AI chat interface backed by OpenAI and SQLite. Discover which apps are used where — instantly!
   
   Keywords:
   n8n, workflow automation, OpenAI, SQLite database, AI assistant, no-code automation, n8n credentials, query workflows, app integrations, chatbot agent, n8n API, Slack workflows, Airtable integrations, Google Sheets workflows, LangChain
   
   Third-party APIs Used:
   
   1. n8n API – for querying workflows and metadata using authentication tokens.
   2. OpenAI – via LangChain/OpenAI-powered AI chat model to interpret natural language queries.
   
   Article:
   
   Unlock Your Workflow Secrets: Exploring n8n Credentials with a Smart AI Assistant
   
   In large-scale workflow automation setups, knowing which app credentials are being used across dozens—or even hundreds—of workflows can be a challenge. Do you know which workflows are using Slack? Which ones are relying on sensitive APIs like OpenAI or Google Sheets? How do you deal with auditing or debugging without meticulously inspecting each workflow manually?
   
   Now, imagine you could ask a simple question like, “Which workflows use Slack and Airtable?” and get a list back in seconds. With the power of n8n, SQLite, and OpenAI’s language model, you can.
   
   Let’s explore how an innovative n8n workflow achieves this—turning your workflow repository into a searchable knowledge base powered by artificial intelligence.
   
   Phase 1: Indexing Workflows and Credentials
   
   The first part of this workflow is all about data collection. It uses n8n’s Manual Trigger to initiate a series of nodes designed to query all workflows available to the user’s n8n API key. This includes:
   
   - Fetching all workflows and parsing each node to extract any associated credentials.
   - Capturing key metadata such as workflow ID and name for easier reference and logging.
   - Formatting the credentials into an easily consumable array, even if multiple nodes use different credential types.
   
   A built-in code node powered by Python then saves this structured information into a local SQLite database. This database is stored in memory and created using SQLite’s lightweight engine through the code module—no external hosting or database system required.
   
   Here’s what makes this smart:
   
   - The actual secret keys from credentials are not exposed. Only credential types and associations are stored.
   - The database is auto-generated and ephemeral by nature—ideal for test environments and compliance.
   - The solution leverages n8n's native "Code" node, showing the power and flexibility of no-code combined with low-code capabilities.
   
   Phase 2: Querying with an AI Agent 🧠
   
   Instead of building search forms and dashboards, the second phase embraces next-gen UX: an AI assistant powered by OpenAI via LangChain. This agent is supercharged by three critical components:
   
   - Chat Trigger: Enables users to enter natural language questions.
   - OpenAI Model: Parses complex queries like “Which workflows use Slack but not Google Sheets?”
   - Query Tool Node: Converts interpreted queries into actual SQL to interrogate the workflow credentials database.
   
   This combination allows you to interact with your workflow repo in a conversational way, almost like talking to a database whisperer. Want to know which workflows are using OpenAI but also mention “AI” in the name? Just ask.
   
   The agent is smart enough to infer your needs. If you mention an app name like “Slack,” it assumes you’re talking about credentials, and it’ll scan available credential metadata in the database accordingly. If asked, it can even generate direct links to the workflows by embedding the workflow_id into a dynamic URL scheme.
   
   Example Use Cases
   
   Here’s what smart queries might look like:
   
   - "Which workflows are using Slack and Google Calendar?"
   - "Are there any workflows using Airtable but not Notion?"
   - "Find workflows with 'AI' in the name but not using OpenAI."
   
   All of this happens in real-time using the chatbot interface, making your workflow repository searchable like never before.
   
   Try It Out in Two Steps:
   
   1. Populate the Database  
   By clicking “Test workflow” and running the initial trigger, n8n fetches all workflows and stores relevant credential mappings in SQLite.
   
   2. Start Chatting  
   Engage with the Workflow Credentials Helper Agent via the chat node. Type your questions and let AI take care of the rest.
   
   Conclusion
   
   By combining robust automation (n8n), lightweight persistence (SQLite), and conversational intelligence (OpenAI), this workflow demonstrates a powerful way to manage and gain insights into your complex workflow ecosystem.
   
   Whether you’re handling integrations with Slack, Google, Airtable, or proprietary APIs, knowing where and how each is used can make your automation infrastructure safer, smarter, and easier to maintain.
   
   Best of all? This is a no-code solution with a touch of Python and generative AI magic. It’s a perfect example of how AI and automation can transform not just what you do—but how you manage it.
   
   Give it a try, and unlock a new way to navigate your workflow universe.
   
   — 
   Written by your friendly AI Assistant ✨

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.