Linkedin Posts MCP server

📝 LinkedIn Posts API: Posts & Engagement to Structured JSON

The most efficient, reliable, and developer-friendly way to use the LinkedIn Posts API.

Actor page: apify.com/johnvc/linkedin-posts-api Input schema: apify.com/johnvc/linkedin-posts-api/input-schema

Give it a public LinkedIn profile URL and it discovers that person's recent posts, or pass specific post URLs to fetch directly. You get back one clean JSON row per post: text, reactions, comments, shares, hashtags, media, and author details. It is built API-first and MCP-ready, so you can call it from Python or drive it as a tool from an AI agent.

Video Walkthrough

Quick Start

Prerequisites

• Python 3.11 or higher
• An Apify account and API key (get a free key here)

1. Clone the repository

git clone https://github.com/johnisanerd/Apify-LinkedIn-Posts-API.git
   cd Apify-LinkedIn-Posts-API

1. Install dependencies with UV

# Install UV if you do not have it:
   curl -LsSf https://astral.sh/uv/install.sh | sh

   # Install project dependencies:
   uv sync

1. Configure your API key

cp .env.example .env
   # Edit .env and add your Apify API key
   # Get your free API key at: https://apify.com?fpr=9n7kx3

1. Run the example

uv run python linkedin-posts-api-example.py

Alternative: set the API key directly

export APIFY_API_TOKEN="your_api_key_here"
uv run python linkedin-posts-api-example.py

Why Use This LinkedIn Posts API?

A URL in, structured data out. You never touch collection infrastructure. Pass a profile URL (or specific post URLs) and get flat, predictable fields you can load straight into a sheet, a database, or a BI tool.

Two ways to collect. Discover a profile's recent posts (newest first, capped and optionally date-filtered), or fetch a known set of posts by URL, up to 1000 per run.

Pay per post. Billing is per post returned, with no per-run setup fee, so you only pay for what is delivered.

Reliable and predictable. Every post comes back with the same field shape, and a profile with no public posts returns a clear error row instead of failing the whole run.

MCP-ready. Call it as a tool from Claude, Cursor, and other AI agents (see the install sections below).

Features

Core Capabilities

• Discover a profile's recent posts by profile URL, or fetch specific posts by URL
• Post text, hashtags, media, and links, plus post type and date
• Reactions, comments, and shares on every post
• Author name, headline, follower count, and a sample of top comments

Data Quality

• One consistent JSON row per post, every time
• A plain-language summary field on every row for quick scanning and AI use
• A clear error row for a profile with no public posts, so one empty profile never sinks the batch

Usage Examples

Discover a profile's posts

{
  "profileUrls": ["https://www.linkedin.com/in/williamhgates"],
  "maxPostsPerProfile": 5
}

Limit discovery to a date range

{
  "profileUrls": ["https://www.linkedin.com/in/williamhgates"],
  "maxPostsPerProfile": 50,
  "startDate": "2025-01-01",
  "endDate": "2025-12-31"
}

Fetch specific posts by URL

{
  "postUrls": [
    "https://www.linkedin.com/posts/williamhgates_activity-7446904645010210816"
  ]
}

Input Parameters

Shortened. The full README is on GitHub.