Most Go High Level users barely scratch the surface of what the platform can do. Yes — GHL is powerful out of the box. You can automate workflows, capture leads, and manage entire sales pipelines.

But what if you could go beyond what the visual automations allow? What if you could connect Go High Level to external data sources, payment platforms, or even AI tools — automatically?

That’s where Python + the Go High Level API comes in.

---

🚀 Why Extend Go High Level with Python?

As your business grows, so does the complexity of your operations. You might want to:

Sync data between GHL and an external CRM or Google Sheet

Generate advanced reports that GHL’s dashboard doesn’t provide

Trigger automations from Stripe, Notion, or Airtable

Use AI to write follow-up messages and push them into GHL automatically

With Python, you can interact directly with Go High Level’s API — giving you total control over data flow, automation logic, and integration.

---

🧩 Understanding the Go High Level API

The Go High Level REST API gives developers access to almost every major function available in your dashboard — including contacts, opportunities, workflows, and more.

The base URL for most endpoints looks like this:

https://services.leadconnectorhq.com

You’ll also need your API key, which can be found in:

Settings → Company → API Key

Keep it secure, as this key gives full access to your account.

---

⚙️ Setting Up Your Python Environment

Before we write any code, make sure Python is installed on your machine. Then install the required package:

pip install requests

Next, create a new Python file (e.g., ghl_api.py) and add this setup code:

import requests
import json

API_KEY = "YOUR_GHL_API_KEY"
BASE_URL = "https://services.leadconnectorhq.com"
HEADERS = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
}

This configuration lets you make secure requests to GHL.

---

📇 Example 1: Fetch All Contacts

You can pull all your contact data into Python for analysis, reporting, or integration.

def get_contacts():
url = BASE_URL + "contacts/"
response = requests.get(url, headers=HEADERS)
data = response.json()
return data.get("contacts", [])

contacts = get_contacts()
print(f"Fetched {len(contacts)} contacts.")

Use Case: Automatically sync your Go High Level contacts with Google >Sheets or another CRM to keep records up to date.

---

💼 Example 2: Create an Opportunity Automatically

Let’s say someone buys your course on Stripe — and you want to automatically create an opportunity in your GHL pipeline.

Here’s how:

def create_opportunity(contact_id, pipeline_id, stage_id, name):
payload = {
"contactId": contact_id,
"pipelineId": pipeline_id,
"stageId": stage_id,
"name": name,
"status": "open"
}
r = requests.post(BASE_URL + "opportunities/", headers=HEADERS, data=json.dumps(payload))
return r.json()

# Example usage
new_opportunity = create_opportunity(
contact_id="abc123",
pipeline_id="xyz789",
stage_id="stage001",
name="New Coaching Client"
)
print(new_opportunity)

Use Case: When a payment webhook from Stripe fires, your Python script can auto-create an opportunity and even assign a follow-up task in GHL.

---

🔁 Example 3: Triggering Workflows Externally

You can also use Python to add contacts to a workflow directly.

def add_contact_to_workflow(contact_id, workflow_id):
payload = {
"contactId": contact_id
}
r = requests.post(BASE_URL + f"workflows/{workflow_id}/execute", headers=HEADERS, data=json.dumps(payload))
return r.json()

result = add_contact_to_workflow("abc123", "workflow_456")
print(result)

Use Case: A student completes a course on Kajabi → Python webhook adds them to a “Graduate Nurture Sequence” workflow in GHL.

---

🧠 Example 4: Using Python + AI with Go High Level

Want to personalize your follow-ups with AI? You can combine OpenAI or Gemini with GHL to generate smart messages automatically.

import openai

openai.api_key = "YOUR_OPENAI_API_KEY"

def generate_followup(name, product):
prompt = f"Write a friendly follow-up message to {name} who recently purchased {product}."
response = openai.Completion.create(
model="gpt-4o-mini",
prompt=prompt,
max_tokens=100
)
return response.choices[0].text.strip()

message = generate_followup("Sarah", "Coaching Accelerator Program")
print(message)

Then push that message into GHL using the contact notes or SMS API endpoints — fully automated.

---

🧰 Real-World Automation Ideas

Here are some ideas you can implement today:

Automated Reports: Run a Python script every Friday to summarize pipeline revenue and send a Slack or email update.

Client Check-Ins: Auto-send a personalized “How’s it going?” text via GHL when a project milestone is reached.

Multi-Platform Sync: Keep your GHL contacts in sync with your Notion or Airtable database using scheduled scripts.

Course Creator Example: After a student finishes a module in your LMS, a Python webhook moves them to the next sequence in GHL.

---

⚠️ Debugging Tips

401 Unauthorized: Your API key may be invalid or expired.

404 Not Found: Double-check endpoint URLs and IDs.

Rate Limits: If you’re making too many requests, use time.sleep() between requests.

Malformed JSON: Always use json.dumps() for payloads.

---

🏁 Conclusion

Go High Level already simplifies client management — but when you combine it with Python, you unlock total automation freedom.

You’re no longer limited to the platform’s built-in tools. You can integrate AI, analytics, and advanced automations that move data between platforms automatically, freeing you up to focus on growth.

---

⚡ Want Help Setting This Up?

If you’d like a custom Python script or API integration for your Go High Level workspace, I can help you:

Build API automations that connect GHL with Stripe, Kajabi, or Airtable

Create AI-powered follow-up systems

Sync your client data automatically

👉 Visit ambrosekol.com to learn more or send a message to discuss your automation project.