# Directory Structure

```
├── .gitignore
├── .python-version
├── pyproject.toml
├── README.md
├── server.py
└── uv.lock
```

# Files

--------------------------------------------------------------------------------
/.python-version:
--------------------------------------------------------------------------------

```
3.12

```

--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------

```
# Python-generated files
__pycache__/
*.py[oc]
build/
dist/
wheels/
*.egg-info

# Virtual environments
.venv
.env

```

--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------

```markdown
# LinkedIn Profile Scraper
This project is a LinkedIn Profile Scraper built using FastMCP and httpx to fetch LinkedIn profile data via the RapidAPI LinkedIn Profile Scraper API.
## Features
+ Retrieves LinkedIn profile data asynchronously.
+ Allows selective inclusion of data like skills, certifications, and more.
+ Uses FastMCP for structured execution.
+ Integrated with Claude Desktop for AI-powered processing.
## Prerequisites
+ A RapidAPI account with access to the LinkedIn Profile Scraper API.
+ A valid RAPIDAPI_KEY.
+ Installed dependencies from requirements.txt.

# Video Link:
https://drive.google.com/file/d/1I3V8SlOgvMgg8hiMxO3Z2lrZl7v00VqM/view?usp=sharing

```

--------------------------------------------------------------------------------
/pyproject.toml:
--------------------------------------------------------------------------------

```toml
[project]
name = "linkedln-mcp"
version = "0.1.0"
description = "Add your description here"
readme = "README.md"
requires-python = ">=3.12"
dependencies = [
    "httpx>=0.28.1",
    "mcp[cli]>=1.4.1",
]

```

--------------------------------------------------------------------------------
/server.py:
--------------------------------------------------------------------------------

```python
from typing import Any
import httpx
import json
from mcp.server.fastmcp import FastMCP
import os
from dotenv import load_dotenv

load_dotenv()

RAPIDAPI_KEY = os.getenv("RAPIDAPI_KEY")
if not RAPIDAPI_KEY:
    raise ValueError("RAPIDAPI_KEY is not set in the environment variables")

mcp = FastMCP("linkedin_profile_scrapper")

LINKEDIN_API_BASE = "https://fresh-linkedin-profile-data.p.rapidapi.com"
RAPIDAPI_HOST = "fresh-linkedin-profile-data.p.rapidapi.com"

async def get_linkedin_data(linkedin_url: str) -> dict[str, Any] | None:
    params = {
        "linkedin_url": linkedin_url,
        "include_skills": "true",
        "include_certifications": "false",
        "include_publications": "false",
        "include_honors": "false",
        "include_volunteers": "false",
        "include_projects": "false",
        "include_patents": "false",
        "include_courses": "false",
        "include_organizations": "false",
        "include_profile_status": "false",
        "include_company_public_url": "false"
    }
    headers = {
        "x-rapidapi-key": RAPIDAPI_KEY,
        "x-rapidapi-host": RAPIDAPI_HOST
    }
    async with httpx.AsyncClient() as client:
        try:
            response = await client.get(
                f"{LINKEDIN_API_BASE}/get-linkedin-profile",
                headers=headers,
                params=params,
                timeout=30.0
            )
            response.raise_for_status()
            return response.json()
        except Exception:
            return None

@mcp.tool()
async def get_profile(linkedin_url: str) -> str:
    data = await get_linkedin_data(linkedin_url)
    if not data:
        return "Unable to fetch LinkedIn profile data."
    return json.dumps(data, indent=2)

if __name__ == "__main__":
    mcp.run(transport="stdio")
```