LinkedIn API Guide

LinkedIn API v2 Endpoints Reference and LinkedIn API Pagination with Start and Count Parameters

January 30, 2025

As the demand for automation in professional networking grows, LinkedIn’s API v2 has become an essential tool for developers and businesses. Whether you’re building marketing automation tools, integrating CRM platforms, or developing business intelligence solutions, understanding LinkedIn’s API endpoints and pagination is critical to success. This guide will walk you through LinkedIn API v2 endpoints and demonstrate how to manage pagination using the start and count parameters effectively.

By the end of this article, you’ll gain the knowledge you need to streamline data retrieval and avoid common pitfalls while building efficient automation tools.

Section 1: LinkedIn API v2 Endpoints Reference

What Are LinkedIn API Endpoints?
API endpoints are specific URLs within LinkedIn’s API that allow developers to interact with LinkedIn’s data and services. Each endpoint serves a unique purpose, such as fetching user profiles, managing connection requests, or sending messages. These endpoints form the backbone of any LinkedIn automation tool, enabling developers to access and manipulate data programmatically.

Key LinkedIn API v2 Endpoints
LinkedIn API v2 offers a variety of endpoints categorized by functionality:

  1. Profile Data
    • Endpoint: GET /me
    • Purpose: Retrieve basic profile information for the authenticated user.
    • Use Case: Display the user’s LinkedIn profile details in an external dashboard or application.
  2. Connections
    • Endpoint: GET /connections
    • Purpose: Fetch a list of first-degree connections for the authenticated user.
    • Use Case: Build CRM tools that integrate LinkedIn connections for business outreach.
  3. Messaging
    • Endpoint: POST /messages
    • Purpose: Send messages to LinkedIn connections.
    • Use Case: Automate outreach campaigns or send follow-up messages to leads.
  4. Content Sharing
    • Endpoint: POST /ugcPosts
    • Purpose: Publish articles, updates, or media on LinkedIn.
    • Use Case: Automate content distribution to engage your LinkedIn audience.

Pro Tip: Each endpoint has specific permissions and requirements. Always review LinkedIn’s API documentation to ensure compliance.

Section 2: LinkedIn API Pagination with Start and Count Parameters

Why Is Pagination Important?
Pagination is a technique that divides large datasets into smaller, manageable chunks, ensuring efficient data retrieval and reducing the risk of exceeding API rate limits. LinkedIn API v2 uses start and count parameters for pagination, allowing developers to fetch data incrementally.

How to Use Start and Count Parameters
The start parameter specifies the offset (starting point) for data retrieval, while the count parameter determines the number of records to fetch in a single request.

Example Request:

GET https://api.linkedin.com/v2/connections?start=0&count=10

Authorization: Bearer YOUR_ACCESS_TOKEN
  • start=0: Begin retrieving data from the first record.
  • count=10: Fetch 10 records per request.

Step-by-Step Implementation

  1. Identify Your Dataset: Determine the total number of records you need to retrieve.
  2. Set Parameters: Use start and count to break the dataset into smaller requests.
  3. Iterate Through Data: Adjust the start value incrementally until all records are retrieved.

Example Code Snippet:

import requests

ACCESS_TOKEN = "YOUR_ACCESS_TOKEN"

BASE_URL = "https://api.linkedin.com/v2/connections"

start = 0

count = 10

while True:

    response = requests.get(

        f"{BASE_URL}?start={start}&count={count}",

        headers={"Authorization": f"Bearer {ACCESS_TOKEN}"}

    )

    data = response.json()

    if "elements" not in data or len(data["elements"]) == 0:

        break

    for connection in data["elements"]:

        print(connection)  # Process each connection

    start += count  # Increment start for the next batch

Best Practices for Pagination

  • Optimize Batch Size: Choose a count value that balances efficiency and rate limits (e.g., 10–50 records).
  • Handle API Limits: Monitor API rate limits and implement retry logic to handle errors gracefully.
  • Process Data in Chunks: Save or process data incrementally to avoid memory overload.

Conclusion

LinkedIn API v2 offers powerful endpoints for automating professional networking, marketing, and business intelligence. By understanding these endpoints and leveraging the start and count parameters for efficient pagination, developers can build robust automation tools while staying within API limits.

Mastering these techniques is essential for anyone looking to harness the full potential of LinkedIn’s API.

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