Skip to main content
Glama
Job Search MCP Server

Job Search MCP Server

by Ritesh-sudo

Job Search MCP Server

An MCP (Model Context Protocol) server that searches across multiple job sites for AI/ML internships and full-time roles with specific filtering criteria.

Features

  • Multi-site Job Search: Searches LinkedIn, Indeed, Glassdoor, ZipRecruiter, and Monster

  • AI/ML Focus: Specifically targets artificial intelligence and machine learning positions

  • Smart Filtering:

    • Filters for entry-level positions (less than 1 year experience)

    • Requires Python proficiency

    • Supports both internships and full-time roles

  • Real-time Results: Gets the latest job postings from all sites

  • Structured Data: Returns well-formatted job information with all relevant details

Related MCP server: JobSpy MCP Server

Installation

  1. Clone or download this repository

  2. Install dependencies:

    npm install
  3. Build the project:

    npm run build

Usage

Running the Server

npm start

Or for development:

npm run dev

Available Tools

1. search_ai_ml_jobs

Search for AI/ML jobs across all supported job sites.

Parameters:

  • location (string, optional): Job location (default: "Remote")

  • maxResults (number, optional): Maximum results to return (default: 50)

  • includeInternships (boolean, optional): Include internships (default: true)

  • includeFullTime (boolean, optional): Include full-time roles (default: true)

  • keywords (array, optional): Additional search keywords

Example:

{
  "location": "San Francisco, CA",
  "maxResults": 25,
  "includeInternships": true,
  "includeFullTime": true,
  "keywords": ["deep learning", "NLP", "computer vision"]
}

2. search_specific_job_site

Search for jobs on a specific job site.

Parameters:

  • site (string, required): Job site ("linkedin", "indeed", "glassdoor", "ziprecruiter", "monster")

  • location (string, optional): Job location (default: "Remote")

  • maxResults (number, optional): Maximum results to return (default: 25)

Example:

{
  "site": "linkedin",
  "location": "Remote",
  "maxResults": 20
}

Job Filtering Criteria

The server automatically applies the following filters:

For Full-time Roles:

  • Experience Level: Entry-level (less than 1 year experience)

  • Required Skills: Must include Python proficiency

  • Job Type: AI/ML related positions only

For Internships:

  • Job Type: AI/ML related positions only

  • Skills: Python proficiency preferred

AI/ML Keywords Detected:

  • Machine Learning

  • Artificial Intelligence

  • Data Science

  • Deep Learning

  • NLP (Natural Language Processing)

  • Computer Vision

  • Neural Networks

  • TensorFlow, PyTorch, Scikit-learn

Response Format

The server returns structured job data including:

{
  "results": [
    {
      "site": "LinkedIn",
      "jobs": [
        {
          "id": "unique_job_id",
          "title": "Machine Learning Engineer",
          "company": "Tech Company",
          "location": "San Francisco, CA",
          "type": "full-time",
          "experienceLevel": "entry",
          "description": "Job description...",
          "requirements": ["Python", "Machine Learning"],
          "skills": ["python", "tensorflow", "pytorch"],
          "postedDate": "2024-01-15T10:30:00Z",
          "applicationUrl": "https://...",
          "source": "LinkedIn",
          "isRemote": false,
          "hasPythonRequirement": true,
          "isAIMLRelated": true
        }
      ],
      "totalFound": 1,
      "searchTime": 1500
    }
  ],
  "totalJobs": 1,
  "searchTimestamp": "2024-01-15T10:30:00Z",
  "filters": {
    "location": "San Francisco, CA",
    "maxResults": 50,
    "includeInternships": true,
    "includeFullTime": true,
    "keywords": [],
    "experienceLevel": "entry",
    "requiredSkills": ["python"],
    "jobTypes": ["ai", "ml", "machine learning", "artificial intelligence", "data science"]
  }
}

Configuration

Copy env.example to .env and modify as needed:

cp env.example .env

Available configuration options:

  • RATE_LIMIT_PER_MINUTE: Rate limiting for requests (default: 30)

  • REQUEST_TIMEOUT: Request timeout in milliseconds (default: 30000)

  • USER_AGENT: User agent string for web scraping

Supported Job Sites

  1. LinkedIn - Professional networking and job board

  2. Indeed - General job search engine

  3. Glassdoor - Job search with company reviews

  4. ZipRecruiter - Job matching platform

  5. Monster - Traditional job board

Technical Details

  • Language: TypeScript

  • Runtime: Node.js

  • Web Scraping: Cheerio for HTML parsing, Axios for HTTP requests

  • Architecture: Modular scraper system with base class and site-specific implementations

Error Handling

The server includes comprehensive error handling:

  • Network timeouts and connection errors

  • HTML parsing errors

  • Rate limiting protection

  • Graceful degradation when individual sites fail

This tool is for educational and personal use. Please respect:

  • Website terms of service

  • Rate limiting to avoid overloading servers

  • Robots.txt files and scraping policies

  • Consider using official APIs when available

Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Add tests for new functionality

  4. Submit a pull request

Available Tools

2 tools
search_ai_ml_jobsC

Search for AI/ML internships and full-time roles across multiple job sites

Inputs: location, maxResults, includeInternships, includeFullTime, +1 more.

search_specific_job_siteC

Search for jobs on a specific job site

Inputs: site (required), location, maxResults.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    C2.8/5.0

    Scored across 2 tools

    Disambiguation2/5

    The two tools have overlapping purposes, as both are for searching jobs, with one being a general AI/ML search and the other for specific sites. This creates ambiguity—an agent might struggle to choose between them when searching on a particular site, as the descriptions don't clearly delineate when to use each tool.

    Naming Consistency4/5

    Both tools follow a consistent snake_case naming pattern with 'search' as the verb, which is predictable and readable. However, the slight inconsistency in naming (e.g., 'search_ai_ml_jobs' vs. 'search_specific_job_site') is minor, as they maintain a clear verb_noun structure.

    Tool Count2/5

    With only 2 tools, the server feels thin for a job search domain, lacking essential operations like filtering, applying, or managing job listings. This limited scope suggests the tool set is underdeveloped and may not support comprehensive agent workflows.

    Completeness2/5

    The tool set is severely incomplete for job searching, missing critical functions such as filtering by location or salary, applying to jobs, saving listings, or tracking applications. This will likely cause agent failures in handling typical job search tasks beyond basic searches.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

    Related MCP Connectors

    Related MCP Servers

    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables AI assistants to search for jobs across multiple platforms (Indeed, LinkedIn, Glassdoor, etc.) using the JobSpy tool, with filtering and structured output.
      128
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables job search and scraping across multiple job boards (LinkedIn, Indeed, Glassdoor, etc.) with advanced filtering, directly from Claude Desktop or other MCP clients.
      6
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables Claude to search AI/ML jobs across Greenhouse, Lever, and Adzuna, with resume tailoring and referral outreach assistance.
      5
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables natural-language job search and aggregation from multiple recruitment websites with zero configuration, providing filtered results and standardized output for AI assistants.
      58 npm
      ISC