search_jobs

Instructions

Implementation Reference

• linkedin_mcp_server/tools/job.py:58-79 (handler)

  The primary handler function for the 'search_jobs' MCP tool. It uses linkedin_scraper.JobSearch to find jobs matching the input search_term, converts Job objects to dictionaries, and handles exceptions with error formatting.

  @mcp.tool()
  async def search_jobs(search_term: str) -> List[Dict[str, Any]]:
      """
      Search for jobs on LinkedIn using a search term.
  
      Args:
          search_term (str): Search term to use for the job search.
  
      Returns:
          List[Dict[str, Any]]: List of job search results
      """
      try:
          driver = safe_get_driver()
  
          logger.info(f"Searching jobs: {search_term}")
          job_search = JobSearch(driver=driver, close_on_complete=False, scrape=False)
          jobs = job_search.search(search_term)
  
          # Convert job objects to dictionaries
          return [job.to_dict() for job in jobs]
      except Exception as e:
          return handle_tool_error_list(e, "search_jobs")

• linkedin_mcp_server/server.py:29-29 (registration)

  Invocation of register_job_tools during MCP server creation, which registers the search_jobs tool (and other job tools) via decorators.

  register_job_tools(mcp)

• linkedin_mcp_server/tools/job.py:24-106 (registration)

  The register_job_tools function defines and registers all job-related tools including search_jobs using @mcp.tool() decorators.

  def register_job_tools(mcp: FastMCP) -> None:
      """
      Register all job-related tools with the MCP server.
  
      Args:
          mcp (FastMCP): The MCP server instance
      """
  
      @mcp.tool()
      async def get_job_details(job_id: str) -> Dict[str, Any]:
          """
          Get job details for a specific job posting on LinkedIn
  
          Args:
              job_id (str): LinkedIn job ID (e.g., "4252026496", "3856789012")
  
          Returns:
              Dict[str, Any]: Structured job data including title, company, location, posting date,
                            application count, and job description (may be empty if content is protected)
          """
          try:
              # Construct clean LinkedIn URL from job ID
              job_url = f"https://www.linkedin.com/jobs/view/{job_id}/"
  
              driver = safe_get_driver()
  
              logger.info(f"Scraping job: {job_url}")
              job = Job(job_url, driver=driver, close_on_complete=False)
  
              # Convert job object to a dictionary
              return job.to_dict()
          except Exception as e:
              return handle_tool_error(e, "get_job_details")
  
      @mcp.tool()
      async def search_jobs(search_term: str) -> List[Dict[str, Any]]:
          """
          Search for jobs on LinkedIn using a search term.
  
          Args:
              search_term (str): Search term to use for the job search.
  
          Returns:
              List[Dict[str, Any]]: List of job search results
          """
          try:
              driver = safe_get_driver()
  
              logger.info(f"Searching jobs: {search_term}")
              job_search = JobSearch(driver=driver, close_on_complete=False, scrape=False)
              jobs = job_search.search(search_term)
  
              # Convert job objects to dictionaries
              return [job.to_dict() for job in jobs]
          except Exception as e:
              return handle_tool_error_list(e, "search_jobs")
  
      @mcp.tool()
      async def get_recommended_jobs() -> List[Dict[str, Any]]:
          """
          Get your personalized recommended jobs from LinkedIn
  
          Returns:
              List[Dict[str, Any]]: List of recommended jobs
          """
          try:
              driver = safe_get_driver()
  
              logger.info("Getting recommended jobs")
              job_search = JobSearch(
                  driver=driver,
                  close_on_complete=False,
                  scrape=True,  # Enable scraping to get recommended jobs
                  scrape_recommended_jobs=True,
              )
  
              if hasattr(job_search, "recommended_jobs") and job_search.recommended_jobs:
                  return [job.to_dict() for job in job_search.recommended_jobs]
              else:
                  return []
          except Exception as e:
              return handle_tool_error_list(e, "get_recommended_jobs")