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Linkedin-Scrap-MCP-Server

@itsShashankSrivastava

リポジトリ

Linkedin-Scrap-MCP-Server について

概要はまだありません

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

itsShashankSrivastava

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "Linkedin-Scrap-MCP-Server": {
      "command": "uv",
      "args": [
        "run",
        "linkedin.py"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Linkedin-Scrap-MCP-Server?

Linkedin-Scrap-MCP-Server is an MCP (Model Context Protocol) server that fetches real-time LinkedIn profile information via the Fresh LinkedIn Profile Data API. It exposes a single tool, get_profile, which accepts a LinkedIn profile URL and returns structured JSON data including skills and other basic public settings. It is intended for developers who need programmatic access to LinkedIn profile data within MCP-compatible applications.

How to use Linkedin-Scrap-MCP-Server?

Clone the repository, install dependencies with uv add mcp[cli] httpx requests, and set the RAPIDAPI_KEY environment variable. Start the server with uv run linkedin.py. Configure your MCP client by adding an entry to config.json with the path to uv and the server directory.

Key features of Linkedin-Scrap-MCP-Server

  • Real-time LinkedIn profile data including skills
  • Asynchronous HTTP requests via httpx
  • Secure API key management with dotenv
  • Single get_profile tool for easy integration
  • Error messages returned on API failures

Use cases of Linkedin-Scrap-MCP-Server

  • Fetch real-time LinkedIn profile information for analysis
  • Retrieve skills and public profile data programmatically
  • Integrate LinkedIn data into MCP-based assistants or agents
  • Automate profile data collection for recruitment or research

FAQ from Linkedin-Scrap-MCP-Server

What is the RAPIDAPI_KEY and how do I get it?

The RAPIDAPI_KEY is required to authenticate requests to the Fresh LinkedIn Profile Data API. You must sign up at RapidAPI, subscribe to that API, and then set the key as an environment variable.

What are the runtime dependencies?

Python 3.7+, the MCP framework, httpx, and python-dotenv are required. The server also uses uv for dependency management and execution.

What happens if the API call fails?

If the LinkedIn API request fails, the get_profile tool returns a clear error message explaining what went wrong. A missing RAPIDAPI_KEY will raise a ValueError.

What data does the get_profile tool return?

It returns structured JSON containing profile details like skills and other basic public settings. Additional extended fields are disabled by default.

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