get_person_profile
Retrieve structured LinkedIn profile data by entering a username to access professional information and connections.
Instructions
Get a specific person's LinkedIn profile.
Args: linkedin_username (str): LinkedIn username (e.g., "stickerdaniel", "anistji")
Returns: Dict[str, Any]: Structured data from the person's profile
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| linkedin_username | Yes |
Input Schema (JSON Schema)
{
"properties": {
"linkedin_username": {
"title": "Linkedin Username",
"type": "string"
}
},
"required": [
"linkedin_username"
],
"type": "object"
}
Implementation Reference
- The core handler function for the 'get_person_profile' tool. Scrapes LinkedIn profile data using linkedin_scraper.Person, structures experiences, educations, skills/interests, accomplishments, and contacts into dictionaries, and returns a comprehensive profile dictionary with error handling.async def get_person_profile(linkedin_username: str) -> Dict[str, Any]: """ Get a specific person's LinkedIn profile. Args: linkedin_username (str): LinkedIn username (e.g., "stickerdaniel", "anistji") Returns: Dict[str, Any]: Structured data from the person's profile """ try: # Construct clean LinkedIn URL from username linkedin_url = f"https://www.linkedin.com/in/{linkedin_username}/" driver = safe_get_driver() logger.info(f"Scraping profile: {linkedin_url}") person = Person(linkedin_url, driver=driver, close_on_complete=False) # Convert experiences to structured dictionaries experiences: List[Dict[str, Any]] = [ { "position_title": exp.position_title, "company": exp.institution_name, "from_date": exp.from_date, "to_date": exp.to_date, "duration": exp.duration, "location": exp.location, "description": exp.description, } for exp in person.experiences ] # Convert educations to structured dictionaries educations: List[Dict[str, Any]] = [ { "institution": edu.institution_name, "degree": edu.degree, "from_date": edu.from_date, "to_date": edu.to_date, "description": edu.description, } for edu in person.educations ] # Convert interests to list of titles interests: List[str] = [interest.title for interest in person.interests] # Convert accomplishments to structured dictionaries accomplishments: List[Dict[str, str]] = [ {"category": acc.category, "title": acc.title} for acc in person.accomplishments ] # Convert contacts to structured dictionaries contacts: List[Dict[str, str]] = [ { "name": contact.name, "occupation": contact.occupation, "url": contact.url, } for contact in person.contacts ] # Return the complete profile data return { "name": person.name, "about": person.about, "experiences": experiences, "educations": educations, "interests": interests, "accomplishments": accomplishments, "contacts": contacts, "company": person.company, "job_title": person.job_title, "open_to_work": getattr(person, "open_to_work", False), } except Exception as e: return handle_tool_error(e, "get_person_profile")
- linkedin_mcp_server/server.py:26-29 (registration)Registers all LinkedIn tools with the MCP server, including the call to register_person_tools(mcp) which adds the get_person_profile tool via its @mcp.tool() decorator.# Register all tools register_person_tools(mcp) register_company_tools(mcp) register_job_tools(mcp)
- linkedin_mcp_server/tools/person.py:20-28 (registration)The registration function for person tools that defines and registers get_person_profile using the @mcp.tool() decorator.def register_person_tools(mcp: FastMCP) -> None: """ Register all person-related tools with the MCP server. Args: mcp (FastMCP): The MCP server instance """ @mcp.tool()