What API does the server use?
It uses the Fresh LinkedIn Profile Data API available through RapidAPI.
@codingaslu
基本信息
This MCP server uses the Fresh LinkedIn Profile Data API to fetch LinkedIn profile information. It is implemented as a model context protocol (MCP) server and exposes a single tool, get_profile, which accepts a LinkedIn profile URL and returns the profile data in JSON format.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"Linkedin_Mcp_Server": {
"command": "uv",
"args": [
"run",
"linkedin.py"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
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。
It is an MCP server that uses the Fresh LinkedIn Profile Data API to fetch LinkedIn profile information. It exposes a single tool, get_profile, which accepts a LinkedIn profile URL and returns the profile data in JSON format.
Install dependencies with uv add mcp[cli] httpx requests. Create a .env file with your RAPIDAPI_KEY. Run the server using uv run linkedin.py. Then configure your MCP client to point to the server, specifying the uv command, the project directory, and the script as arguments.
httpx)dotenv)get_profile toolIt uses the Fresh LinkedIn Profile Data API available through RapidAPI.
You need Python 3.7+, the MCP framework, installed dependencies (`httpx`, `python-dotenv`, etc.), and a valid `RAPIDAPI_KEY`.
Obtain an API key from [RapidAPI](https://rapidapi.com/) and add it to a `.env` file or set it in your environment.
The server will raise a `ValueError` indicating the key is missing.
The `get_profile` tool returns a message indicating that the profile data could not be fetched.
MCP server for fetch web page content using Playwright headless browser.
Give your AI agent the live web. One MCP server for Search, Fetch, Browser, and Agent: browse real sites, extract structured data, fill forms, and run multi-step workflows. Search and Fetch are free.
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