List endpoints return results in pages. Every list response has the same shape: a data array and a meta object describing the page.
Parameters
| Parameter | Type | Default | Notes |
|---|
page | integer | 1 | The 1-based page number. |
pageSize | integer | 25 | Items per page. Maximum 100. |
curl "https://backend.leadey.ai/v1/leads?page=2&pageSize=50" \
-H "Authorization: Bearer $LEADEY_API_KEY"
Response shape
{
"data": [ /* … up to pageSize items … */ ],
"meta": {
"page": 2,
"pageSize": 50,
"totalCount": 134,
"totalPages": 3
}
}
totalCount — total items matching the query across all pages.totalPages — ceil(totalCount / pageSize). You’ve reached the end when page >= totalPages.
Iterating every page
Request pages until you’ve seen totalPages:
import os, requests
headers = {"Authorization": f"Bearer {os.environ['LEADEY_API_KEY']}"}
page, leads = 1, []
while True:
r = requests.get(
"https://backend.leadey.ai/v1/leads",
headers=headers,
params={"page": page, "pageSize": 100},
).json()
leads.extend(r["data"])
if page >= r["meta"]["totalPages"]:
break
page += 1
print(f"Fetched {len(leads)} leads")
Use the largest pageSize (100) to minimise round trips, and combine it with filters like search, status, or campaignId to narrow results before paging.
