What API does the server use?
It uses the Fresh LinkedIn Profile Data API available through RapidAPI.
@codingaslu
Basic information
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.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"Linkedin_Mcp_Server": {
"command": "uv",
"args": [
"run",
"linkedin.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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