LinkedIn Profile Analyzer MCP Server

Analyzes LinkedIn profiles by fetching, filtering, and managing post data, designed for integration with Claude AI.

Local serverstdioPython 31

What is the LinkedIn Profile Analyzer MCP server?

LinkedIn Profile Analyzer MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Analyzes LinkedIn profiles by fetching, filtering, and managing post data, designed for integration with Claude AI.

What you get

A powerful LinkedIn profile analyzer MCP (Model Context Protocol) server that interacts with LinkedIn's API to fetch, analyze, and manage LinkedIn posts data. This MCP is specifically designed to work with Claude AI.

  • Fetch and store LinkedIn posts for any public profile
  • Search through posts with keyword filtering
  • Get top performing posts based on engagement metrics
  • Filter posts by date range
  • Paginated access to stored posts
  • Easy integration with Claude AI

What the assistant can call

Once LinkedIn Profile Analyzer is connected, these are the calls the assistant has available:

  • x-rapidapi-key — Your RapidAPI key
  • x-rapidapi-host — linkedin-data-api.p.rapidapi.com

Setting it up

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.

Configuration and credentials

You will need one environment variable: RAPIDAPI_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

  • Python 3.7+ - RapidAPI key for LinkedIn Data API - Claude AI access

Choosing this one

Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. LinkedIn Profile Analyzer's toolset — x-rapidapi-key, x-rapidapi-host — is a fair guide to whether it matches your workflow. It is maintained by rugvedp; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the linkedin profile analyzer mcp server does with a few real requests.

Available tools

ToolWhat it does
x-rapidapi-keyYour RapidAPI key
x-rapidapi-hostlinkedin-data-api.p.rapidapi.com

How to install the LinkedIn Profile Analyzer MCP server

{
  "mcpServers": {
    "LinkedIn Updated": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "path/to/your/script.py"
      ]
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Python 3.7+ - RapidAPI key for LinkedIn Data API - Claude AI access
VariableDescriptionRequired
RAPIDAPI_KEYCredential the server authenticates with.Yes

Example prompts to try

  • Use LinkedIn Profile Analyzer to x-rapidapi-key.
  • Use LinkedIn Profile Analyzer to x-rapidapi-host.

Frequently asked questions

Key features include fetching and storing posts, keyword filtering, identifying top-performing posts based on engagement, date range filtering, and paginated access.