🔎 LinkedIn Post Search API: Search LinkedIn Posts by Keyword from Python and MCP

LinkedIn post search by keyword, name, phrase or #hashtag: get every matching public post as JSON, with the full text, author, date, reactions, comments, images and links. No LinkedIn login, no cookie.

• Actor: LinkedIn Post Search API on Apify
• Input schema: input parameters
• Get a free API token: apify.com

This repo is a Python and MCP quick-start for the LinkedIn Post Search API on Apify. Give it keywords, names or hashtags and a date window such as the past day or the past week, and it returns the public LinkedIn posts that mention them, one row per post. It is the search LinkedIn itself only offers to logged-in members, run as an API over the public side of LinkedIn: no account, no session cookie, nothing attributed to you. Run it on a schedule and it becomes a LinkedIn social listening feed; run it once with a date range and it is research for a story, a launch or an event.

Coverage is the public, indexed part of LinkedIn. Posts from members who keep their activity private, and posts published in the last few hours, may be missing, and a signed-out visitor sees at most 10 comments per post. For a mention monitor that is usually what you want: the posts that are public and spreading.

Responsible use: the API returns only what LinkedIn shows signed-out visitors and collects no contact details, and you are responsible for using the data lawfully.

Video Walkthrough

Text walkthrough

The LinkedIn Post Search API turns a keyword into a list of public LinkedIn posts. You pass keywords (up to 20 names, phrases or #hashtags, each matched as an exact phrase), pick postedWithin (day, week, month, year) or a startDate and endDate, and cap the run with maxPostsPerKeyword. Each row carries text, authorName, authorUrl, authorType, datePosted, numLikes, numComments, topComments, hashtags, images, embeddedLinks, taggedPeople and taggedCompanies, plus matchedKeyword and the search page and rank it came from. For LinkedIn hashtag analytics, pass #semiconductors with postedWithin: "week" and sort the rows by numLikes to see which posts and authors lead the tag; for brand monitoring, pass your company and your executives with postedWithin: "day" on a daily schedule. The default run in this repo asks for five posts about one event and costs well under a cent; posts and search pages read in the last 7 days come back from a shared cache, so repeats are cheaper and faster.

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-Post-Search-API.git
   cd Apify-LinkedIn-Post-Search-API
   

2. 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
   

3. 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
   

4. Run the example

   uv run python linkedin-post-search-api-example.py
   

The script starts one run for "Jackson Hole Symposium" with maxPostsPerKeyword: 5, waits for it to finish, prints each post with its author, date, reactions and link, and then prints the run's RUN_SUMMARY (pages fetched, cache hits, why each keyword stopped). Three recipe helpers mirror the use cases on the Actor's Examples tab:

uv run python linkedin-post-s

... [View full README on GitHub](https://github.com/johnisanerd/apify-linkedin-post-search-api#readme)