Is Linkedin Post Engager Capture free?

Yes, Linkedin Post Engager Capture is free to use.

How do I install Linkedin Post Engager Capture?

Linkedin Post Engager Capture is a local plugin. Install it using npm package: @mambalabsdev/mcp-linkedin-post-engager-capture and add the generated configuration snippet to your AI app's MCP config file. Then restart your AI app.

Is Linkedin Post Engager Capture safe to use?

Yes. Linkedin Post Engager Capture passed MCP Marketplace's automated security scan with a score of 10/10 (low risk). Every server on MCP Marketplace is security-scanned before it's listed; see the full security report on this page for the findings and permissions.

What credentials does Linkedin Post Engager Capture need?

Linkedin Post Engager Capture requires the following credentials or environment variables: APIFY_TOKEN. You can find setup instructions on the server detail page.

What AI apps work with Linkedin Post Engager Capture?

Linkedin Post Engager Capture uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Linkedin Post Engager Capture MCP Server

by mambabuilt

Marketing & SocialLow Risk10.0Local

Free

Collect the LinkedIn posts a search engine has indexed for profiles and company pages.

About

Collect the LinkedIn posts a search engine has indexed for profiles and company pages.

Security Report

10.0

Low Risk10.0Low Risk

Valid MCP server (2 strong, 3 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry. Trust signals: trusted author (57/57 approved).

7 files analyzed · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

file_system

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Check that this permission is expected for this type of plugin.

Shell Command Execution

Runs commands on your machine. Be cautious — only use if you trust this plugin.

What You'll Need

Set these up before or after installing:

Apify API token from https://console.apify.com/account/integrationsRequired

Environment variable: APIFY_TOKEN

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "com-mambabuilt-mcp-linkedin-post-engager-capture": {
      "env": {
        "APIFY_TOKEN": "your-apify-token-here"
      },
      "args": [
        "-y",
        "@mambalabsdev/mcp-linkedin-post-engager-capture"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

LinkedIn Post Tracker MCP Server

MCP server for the Mamba Labs LinkedIn Post Tracker actor on Apify.

Point it at LinkedIn person profiles or company pages. It returns the posts a search engine has indexed for each one, as flat rows: permalink, author, a text excerpt, and the publish date. No request is sent to LinkedIn, and no cookie, account, or credential is used.

Changed in 1.3.0. The actor stopped fetching linkedin.com on 2026-10-12. Commenter rows, reaction and comment counts, media, and the inputs collect_commenters, collect_reactors, max_engagers_per_post, and use_residential_proxy are gone. Posts now come from search results, so coverage is what the index holds: posts appear days or weeks after publishing, and many never appear. The tool keeps its name, capture_linkedin_posts_and_commenters, so existing clients keep working.

Install

npx -y @mambalabsdev/mcp-linkedin-post-engager-capture

Claude Desktop

{
  "mcpServers": {
    "mamba-linkedin-post-engager-capture": {
      "command": "npx",
      "args": ["-y", "@mambalabsdev/mcp-linkedin-post-engager-capture"],
      "env": { "APIFY_TOKEN": "your-apify-token" }
    }
  }
}

Get an Apify token at console.apify.com/account/integrations.

Tool

`capture_linkedin_posts_and_commenters`

LinkedIn profiles and company pages in, the posts a search engine has indexed for them out.

Input	Type	Required	Meaning
`profile_urls`	array of strings	one of the two	Person profiles, for example `https://www.linkedin.com/in/williamhgates`.
`company_urls`	array of strings	one of the two	Company pages, for example `https://www.linkedin.com/company/microsoft`.
`posted_since`	string	no	ISO date. Posts published before this are skipped before anything is charged.

Reading the output

post is one row per indexed post: post_id, post_permalink, author_name, author_url, author_type, post_text (the search engine's excerpt), published_at (decoded from the post id).
notice is a run-level or source-level message. Filter these out before loading a table.

A post counts only when its permalink names the source, for example linkedin.com/posts/stripe_... for linkedin.com/company/stripe. A refused search comes back as a degraded notice, never as "no posts".

Billing

You are charged per post collected, plus a small actor start fee. Notice rows are free. posted_since filters before anything is charged.

Event	Price per event (USD)	Fires when
`apify-actor-start`	$0.00005	Charged when the Actor starts running, one event per GB of memory.
`post-collected`	$0.002 on the Free plan, down to $0.0017 on higher Apify plans	One LinkedIn post returned from search results, with its permalink, author, text excerpt and publish date.

The actor's Apify page carries the current prices.

What this server does and does not do

It is a thin client for the Apify actor. It passes your input through and returns the actor's output unchanged. Every behavior described above lives in the actor, not here.

It reads only public search engine results. It sends no request to LinkedIn, holds no session cookie, and uses no LinkedIn account.

Post rows from a person profile name that person. When you run this you are the data controller for the personal data it returns and Apify is the processor. Your lawful basis is yours to establish; nothing here is legal advice.

This actor is unofficial and is not affiliated with, sponsored by or endorsed by LinkedIn or Microsoft.

Errors are surfaced, never swallowed. An invalid input, an invalid token, an exhausted balance, a timeout, or a run that returns anything other than a dataset all come back as an explicit tool error rather than as an empty result.