This article provides a complete, practical walkthrough of the Http Github Create Webhook 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:  
   Automated Lead Generation from GitHub Forks Using n8n and Pipedrive
   
   Meta Description:  
   Learn how to automate lead creation in Pipedrive CRM whenever someone forks your GitHub repository using a no-code n8n workflow integrated with GitHub and Pipedrive APIs.
   
   Keywords:  
   n8n workflow, GitHub automation, Pipedrive integration, CRM automation, no-code lead generation, GitHub trigger, Pipedrive API, automate sales funnel, GitHub forks to leads, sales automation workflow
   
   Third-party APIs Used:
   
   1. GitHub API
   2. Pipedrive API
   
   Article:
   
   In today’s fast-paced, automation-centric world, connecting different platforms to streamline lead generation is not a luxury—it’s a necessity. One powerful use case is transforming GitHub activity into actionable sales data. With the no-code/low-code automation tool n8n, you can integrate platforms like GitHub and Pipedrive to create a seamless workflow that transforms every fork of your repository into a potential lead.
   
   This article explores a practical n8n workflow that automatically creates a lead in Pipedrive every time someone forks a GitHub repository. Let’s take a closer look at how this automation works under the hood.
   
   👩‍💻 The Use Case
   
   When a developer forks your public GitHub repo—for example, a demo product or open-source solution—it’s usually a sign of interest. By capturing this moment and turning it into a Pipedrive lead, you can start personalizing outreach, track interest, and nurture this contact through your sales funnel.
   
   The workflow is built in n8n and connects GitHub and Pipedrive using their respective APIs.
   
   🔗 Key Workflow Steps
   
   1. GitHub Webhook Trigger (On fork)
   
   The workflow begins with a GitHub Trigger node that listens for “fork” events on a specified GitHub repo (in this case, "DemoRepo" under the GitHub user "John-n8n"). The trigger activates whenever a user forks the repository.
   
   2. Get GitHub User Information
   
   Once the trigger fires, the workflow moves to retrieving more information about the user who forked the repo. Using the HTTP Request node authenticated via GitHub credentials, it makes an API call to the user’s GitHub profile URL.
   
   3. Search for Forkee in Pipedrive
   
   With the forkee's email (if available from GitHub), the workflow then checks if this person already exists in the Pipedrive CRM. It uses the Pipedrive "Search" node to search users by their email address.
   
   4. Conditional Check – Person Exists?
   
   The workflow uses a Boolean "IF" node to determine whether the person was found in the CRM (i.e., if the name field is not empty). Based on the results, the automation splits into one of two paths:
   
   - If the person already exists: Proceed to lead creation.
   - If the person doesn’t exist: Create a new person in Pipedrive first.
   
   5. Create or Set Person in Pipedrive
   
   - If the person does not yet exist in Pipedrive, a "Create person" node is used to add them, using their GitHub login as the name and their email (if retrievable).
   - After creating or verifying an existing person, their ID is extracted and set using the "Set" node for use in the lead creation step.
   
   6. Create Lead in Pipedrive
   
   A new lead is created in Pipedrive with a title indicating which repo was forked and by whom. The lead is automatically associated with the person's ID in the CRM.
   
   Example title:  
   Repo 'John-n8n/DemoRepo' forked by JaneDoe
   
   7. Create Note With GitHub Profile URL
   
   Finally, the workflow adds a note to the lead that includes the GitHub URL of the user. This is helpful for your sales or outreach team to view the developer’s GitHub profile for further context.
   
   📈 Benefits of This Automation
   
   - Immediate capture of developer interest
   - Reduction in manual CRM data entry
   - Real-time data syncing between GitHub and Pipedrive
   - Better lead qualification based on developer behavior
   - Personalized communication using enriched GitHub data
   
   🔒 Data Considerations
   
   While GitHub provides public user information, not all profiles expose emails. In such cases, creating the person in Pipedrive may require fallback logic or manual follow-up.
   
   🔧 Tools and APIs Used
   
   - GitHub API – Used to listen to repository fork events and retrieve user information.
   - Pipedrive API – Used to create persons, leads, and notes in the CRM.
   
   🧩 Extendability
   
   This workflow can be further enhanced to:
   - Add tags or labels based on repos forked.
   - Assign leads to a specific sales rep based on region or tech stack.
   - Send customized emails via another service such as SendGrid or Gmail.
   
   🛠 Wrap-up
   
   Automating lead generation from GitHub activity can fill your sales pipeline with qualified technical users who’ve already shown interest in your products or tools. With n8n, integrating GitHub and Pipedrive is both efficient and scalable—enabling real-time CRM updates with no manual intervention.
   
   By harnessing this kind of automation, your sales team can act on warm leads faster, personalize outreach with GitHub insights, and ultimately close deals more effectively.
   
   Ready to automate your sales funnel? Try building this workflow in n8n today.

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.