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    Jobspy Mcp Server

    MCP server to search for jobs across multiple job listing platforms

    13 stars
    JavaScript
    Updated Oct 26, 2025

    Table of Contents

    • Features
    • Prerequisites
    • Installation
    • Configuration
    • Environment Variables
    • Setting Up Configuration
    • 1. Using environment variables directly
    • 2. Using a .env file
    • Usage
    • Starting the server
    • Connecting with Claude Desktop
    • Using with Web Clients (SSE Transport)
    • API Usage
    • Search Jobs
    • Available Tools
    • search_jobs
    • Docker Support
    • Development
    • Running in development mode
    • Running tests
    • License

    Table of Contents

    • Features
    • Prerequisites
    • Installation
    • Configuration
    • Environment Variables
    • Setting Up Configuration
    • 1. Using environment variables directly
    • 2. Using a .env file
    • Usage
    • Starting the server
    • Connecting with Claude Desktop
    • Using with Web Clients (SSE Transport)
    • API Usage
    • Search Jobs
    • Available Tools
    • search_jobs
    • Docker Support
    • Development
    • Running in development mode
    • Running tests
    • License

    Documentation

    JobSpy MCP Server

    A Model Context Protocol (MCP) server that enables AI assistants like Claude to search for jobs across multiple job listing platforms using the JobSpy tool.

    Features

    • Search for jobs across multiple platforms (Indeed, LinkedIn, Glassdoor, etc.)
    • Filter by search terms, location, time frames, and more
    • Get structured job data that AI models can easily process
    • Format results as JSON or CSV
    • Multiple transport options: stdio for Claude integration, SSE for web clients

    Prerequisites

    • Node.js 16+
    • Python 3.6+
    • The JobSpy tool installed and available

    Installation

    bash
    # Clone the repository
    git clone https://github.com/borgius/jobspy-mcp-server.git
    cd jobspy-mcp-server
    
    # Install dependencies
    npm install
    
    # Make sure the JobSpy tool is properly set up
    cd ../jobSpy
    pip install -r requirements.txt
    chmod +x run.sh

    Configuration

    The server will automatically try to locate the JobSpy script in standard locations:

    • ../jobSpy/run.sh (relative to the server directory)
    • ./run.sh (in the current directory)
    • /app/run.sh (for Docker environments)

    Environment Variables

    You can configure the server using the following environment variables:

    Environment VariableDescriptionDefault
    JOBSPY_DOCKER_IMAGEDocker image to use for JobSpyjobspy
    JOBSPY_ACCESS_TOKENAccess token for JobSpy API (if required)none
    PORTPort for the MCP server9423
    HOSTHost for HTTP server'0.0.0.0'
    ENABLE_SSEEnable Server-Sent Events transport0

    Setting Up Configuration

    You can set these configuration values in multiple ways:

    1. Using environment variables directly

    bash
    export JOBSPY_DOCKER_IMAGE=jobspy
    export JOBSPY_HOST='0.0.0.0'
    export JOBSPY_PORT=9423
    export ENABLE_SSE=1

    2. Using a .env file

    Create a .env file in the root directory with your configuration:

    code
    JOBSPY_DOCKER_IMAGE=jobspy
    JOBSPY_HOST='0.0.0.0'
    JOBSPY_PORT=9423
    ENABLE_SSE=1

    Usage

    Starting the server

    bash
    npm start

    Connecting with Claude Desktop

    Add the following to your Claude Desktop config file (typically at ~/Library/Application Support/Claude/claude_desktop_config.json):

    json
    {
      "mcpServers": {
        "jobspy": {
          "command": "node",
          "args": ["/path/to/jobspy-mcp-server/src/index.js"],
          "env": {
            "ENABLE_SSE": 0
          }
        }
      }
    }

    Using with Web Clients (SSE Transport)

    The server exposes HTTP endpoints that allow web applications to interact with the JobSpy MCP server:

    • Connect for updates: GET /mcp/connect
    • Establishes a Server-Sent Events (SSE) connection for real-time updates
    • Returns progress updates and job search results
    • Send requests: POST /mcp/request
    • Accepts tool invocation requests in MCP format
    • Returns tool responses

    Example JavaScript client for browser:

    javascript
    // Connect to SSE endpoint
    const eventSource = new EventSource('http://localhost:9423/mcp/connect');
    
    // Listen for updates
    eventSource.onmessage = function(event) {
      const data = JSON.parse(event.data);
      console.log('Received update:', data);
      
      // Handle progress updates
      if (data.type === 'progress') {
        updateProgressBar(data.progress);
      }
    };
    
    // Send a search request
    async function searchJobs() {
      const response = await fetch('http://localhost:9423/mcp/request', {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json'
        },
        body: JSON.stringify({
          tool: 'search_jobs',
          params: {
            search_term: 'software engineer',
            location: 'San Francisco, CA',
            site_names: 'indeed,linkedin'
          }
        })
      });
      
      return await response.json();
    }

    API Usage

    The server exposes the following endpoints:

    Search Jobs

    code
    GET /search

    Query parameters:

    • site_names: Comma-separated list of job sites to search
    • search_term: Term to search for
    • location: Job location
    • And other JobSpy parameters as needed

    Available Tools

    search_jobs

    Searches for jobs across various job listing websites.

    Parameters:

    ParameterTypeDescriptionDefault
    site_namesstringComma-separated list of job sites to search (indeed,linkedin,zip_recruiter,glassdoor,google,bayt,naukri)"indeed"
    search_termstringSearch term for jobs"software engineer"
    locationstringLocation for job search"San Francisco, CA"
    google_search_termstringGoogle specific search termnull
    results_wantedintegerNumber of results wanted20
    hours_oldintegerHow many hours old the jobs can be72
    country_indeedstringCountry for Indeed search"USA"
    linkedin_fetch_descriptionbooleanWhether to fetch LinkedIn job descriptions (slower)false
    formatstringOutput format (json or csv)"json"
    outputstringOutput filename without extension"jobs"

    Example usage with Claude:

    code
    I need to find senior software engineer jobs in Boston posted in the last 24 hours on both LinkedIn and Indeed.

    Docker Support

    A Dockerfile is provided to containerize the MCP server:

    bash
    # Build the Docker image
    docker build -t jobspy-mcp-server .
    
    # Run the container
    docker run -p 9423:9423 jobspy-mcp-server

    Development

    Running in development mode

    bash
    npm run dev

    Running tests

    bash
    npm test
    bash
    curl -X POST "http://localhost:9423/api" \
      -H "Content-Type: application/json" \
      -d '{
        "method": "search_jobs",
        "params": {
          "search_term": "software engineer",
          "location": "San Francisco, CA",
          "site_names": "indeed,linkedin",
          "results_wanted": 10,
          "format": "json"
        }
      }'

    License

    MIT

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