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Linkedin-Scrap-MCP-Server

@itsShashankSrivastava

代码仓库

关于 Linkedin-Scrap-MCP-Server

暂无概览

基本信息

分类

其他

运行时

python

传输方式

stdio

发布者

itsShashankSrivastava

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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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