> ## Documentation Index
> Fetch the complete documentation index at: https://api.leadey.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Pagination

> Page through large result sets with page and pageSize.

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`. |

```bash theme={"dark"}
curl "https://backend.leadey.ai/v1/leads?page=2&pageSize=50" \
  -H "Authorization: Bearer $LEADEY_API_KEY"
```

## Response shape

```json theme={"dark"}
{
  "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`:

```python theme={"dark"}
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")
```

<Tip>
  Use the largest `pageSize` (100) to minimise round trips, and combine it with filters like `search`, `status`, or `campaignId` to narrow results before paging.
</Tip>