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Job Search

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@Amoghpurohit

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Job Search MCP Skill

This skill enables AI agents to search for jobs across multiple job boards using the JobSpy MCP Server. JobSpy aggregates job listings from LinkedIn, Indeed, Glassdoor, ZipRecruiter, Google Jobs, Bayt, Naukri, and BDJobs into a unified interface.

When to Use This Skill

Use this skill when the user asks you to:

  • Find job listings matching specific criteria (role, location, company, etc.)
  • Search for remote or on-site positions
  • Compare job opportunities across different platforms
  • Get salary information for job postings
  • Find recently posted jobs (within X hours)
  • Search for jobs with "Easy Apply" options

Prerequisites

  • Python 3.10+
  • Node.js 16+ (for some server implementations)
  • The JobSpy MCP server installed and configured

Installation & Setup

Option 1: Python MCP Server (Recommended)

# Install with pip
pip install mcp>=1.1.0 python-jobspy>=1.1.82 pandas>=2.1.0 pydantic>=2.0.0

# Or install with uv (faster)
uv add mcp python-jobspy pandas pydantic

Option 2: Clone a Pre-built Server

# Clone the jobspy-mcp-server repository
git clone https://github.com/chinpeerapat/jobspy-mcp-server.git
cd jobspy-mcp-server

# Install dependencies
uv sync
# or
pip install -e .

Claude Desktop Configuration

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

{
  "mcpServers": {
    "jobspy": {
      "command": "uv",
      "args": ["run", "jobspy-mcp-server"],
      "env": {}
    }
  }
}

Alternative configuration (Node.js server):

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

MCP Tool Schemas

1. scrape_jobs_tool (Primary Tool)

Search for jobs across multiple job boards with comprehensive filtering.

Parameters:

ParameterTypeRequiredDefaultDescription
search_termstring✅ Yes-Job keywords (e.g., "software engineer", "data scientist")
locationstringNo-Job location (e.g., "San Francisco, CA", "Remote")
site_namearrayNo["indeed", "linkedin", "zip_recruiter", "google"]Job boards to search
results_wantedintegerNo15Number of results (1-1000)
job_typestringNo-Employment type: fulltime, parttime, internship, contract
is_remotebooleanNofalseFilter for remote jobs only
hours_oldintegerNo-Filter by posting recency in hours
distanceintegerNo50Search radius in miles (1-100)
easy_applybooleanNofalseFilter jobs with easy apply option
country_indeedstringNo"usa"Country for Indeed/Glassdoor searches
linkedin_fetch_descriptionbooleanNofalseFetch full LinkedIn descriptions (slower)
offsetintegerNo0Pagination offset
verboseintegerNo1Logging level (0=errors, 1=warnings, 2=all)

Supported Values for site_name:

  • linkedin - Professional networking platform (rate limited)
  • indeed - Largest job search engine (most reliable)
  • glassdoor - Jobs with company reviews and salaries
  • zip_recruiter - Job matching for US/Canada
  • google - Aggregated job listings
  • bayt - Middle East job portal
  • naukri - India's leading job portal
  • bdjobs - Bangladesh job portal

Supported Values for job_type:

  • fulltime
  • parttime
  • internship
  • contract

2. get_supported_countries

Returns the complete list of supported countries for job searches. No parameters required.

3. get_supported_sites

Returns detailed information about all supported job board sites. No parameters required.

4. get_job_search_tips

Returns tips and best practices for effective job searching. No parameters required.


Job Post Response Schema

When jobs are returned, each job post contains the following fields:

interface JobPost {
  // Core fields (all platforms)
  title: string;                    // Job title
  company: string;                  // Company name
  company_url?: string;             // Company website URL
  job_url: string;                  // Direct link to job posting
  location: {
    country?: string;
    city?: string;
    state?: string;
  };
  is_remote: boolean;               // Whether job is remote
  description?: string;             // Job description (markdown format)
  job_type?: "fulltime" | "parttime" | "internship" | "contract";
  
  // Salary information
  salary?: {
    interval?: "yearly" | "monthly" | "weekly" | "daily" | "hourly";
    min_amount?: number;
    max_amount?: number;
    currency?: string;
    salary_source?: "direct_data" | "description";  // Parsed from posting
  };
  
  date_posted?: string;             // ISO date string
  emails?: string[];                // Contact emails if available
  
  // LinkedIn specific
  job_level?: string;               // Seniority level
  
  // LinkedIn & Indeed specific
  company_industry?: string;
  
  // Indeed specific
  company_country?: string;
  company_addresses?: string[];
  company_employees_label?: string;
  company_revenue_label?: string;
  company_description?: string;
  company_logo?: string;
  
  // Naukri specific
  skills?: string[];
  experience_range?: string;
  company_rating?: number;
  company_reviews_count?: number;
  vacancy_count?: number;
  work_from_home_type?: string;
}

Example Prompts → MCP Calls → Outputs

Example 1: Basic Job Search

User Prompt:

"Find me 10 software engineer jobs in San Francisco"

MCP Tool Call:

{
  "tool": "scrape_jobs_tool",
  "params": {
    "search_term": "software engineer",
    "location": "San Francisco, CA",
    "results_wanted": 10,
    "site_name": ["indeed", "linkedin"]
  }
}

Expected Output:

{
  "jobs": [
    {
      "title": "Software Engineer",
      "company": "TechCorp Inc.",
      "location": { "city": "San Francisco", "state": "CA" },
      "job_url": "https://indeed.com/viewjob?jk=abc123",
      "salary": { "min_amount": 120000, "max_amount": 180000, "interval": "yearly" },
      "job_type": "fulltime",
      "is_remote": false
    }
    // ... more jobs
  ],
  "total_found": 10
}

Example 2: Remote Jobs Search

User Prompt:

"Search for remote Python developer positions from Indeed and ZipRecruiter"

MCP Tool Call:

{
  "tool": "scrape_jobs_tool",
  "params": {
    "search_term": "Python developer",
    "location": "Remote",
    "is_remote": true,
    "site_name": ["indeed", "zip_recruiter"],
    "results_wanted": 20
  }
}

Example 3: Recent Jobs with Filters

User Prompt:

"Find data scientist jobs in Boston posted in the last 24 hours"

MCP Tool Call:

{
  "tool": "scrape_jobs_tool",
  "params": {
    "search_term": "data scientist",
    "location": "Boston, MA",
    "hours_old": 24,
    "site_name": ["linkedin", "glassdoor", "indeed"],
    "linkedin_fetch_description": true
  }
}

Example 4: Entry-Level with Easy Apply

User Prompt:

"Look for entry-level marketing jobs in New York with easy apply options"

MCP Tool Call:

{
  "tool": "scrape_jobs_tool",
  "params": {
    "search_term": "junior marketing",
    "location": "New York, NY",
    "job_type": "fulltime",
    "easy_apply": true,
    "site_name": ["indeed", "zip_recruiter"],
    "results_wanted": 30
  }
}

Example 5: International Job Search

User Prompt:

"Find software jobs in Germany on Indeed"

MCP Tool Call:

{
  "tool": "scrape_jobs_tool",
  "params": {
    "search_term": "software developer",
    "location": "Berlin",
    "country_indeed": "germany",
    "site_name": ["indeed"],
    "results_wanted": 15
  }
}

Example 6: Getting Helper Information

User Prompt:

"What job sites are supported?"

MCP Tool Call:

{
  "tool": "get_supported_sites",
  "params": {}
}

Expected Output:

{
  "sites": [
    { "name": "indeed", "description": "Largest job search engine, most reliable" },
    { "name": "linkedin", "description": "Professional networking platform, rate limited" },
    { "name": "glassdoor", "description": "Jobs with company reviews and salaries" },
    { "name": "zip_recruiter", "description": "Job matching for US/Canada" },
    { "name": "google", "description": "Aggregated job listings" },
    { "name": "bayt", "description": "Middle East job portal" },
    { "name": "naukri", "description": "India's leading job portal" },
    { "name": "bdjobs", "description": "Bangladesh job portal" }
  ]
}

Error Handling Examples

Error 1: Rate Limiting

Scenario: LinkedIn returns a rate limit error.

Error Response:

{
  "error": "RateLimitError",
  "message": "LinkedIn rate limit exceeded. Try again later or use different sites.",
  "suggestion": "Switch to Indeed or ZipRecruiter which have more lenient rate limits."
}

How to Handle:

  • Reduce results_wanted to a smaller number (10-15)
  • Remove linkedin from site_name temporarily
  • Add delays between searches
  • Use proxy configuration if available

Error 2: No Results Found

Scenario: Search returns empty results.

Error Response:

{
  "jobs": [],
  "total_found": 0,
  "message": "No jobs found matching your criteria"
}

How to Handle:

  • Broaden search terms (e.g., "engineer" instead of "senior principal software engineer")
  • Increase distance radius
  • Remove restrictive filters like hours_old or job_type
  • Try different site_name options
  • Check if location spelling is correct

Error 3: Invalid Country Code

Scenario: User specifies an unsupported country for Indeed.

Error Response:

{
  "error": "ValidationError",
  "message": "Invalid country_indeed value. Use get_supported_countries to see valid options."
}

How to Handle:

  • Call get_supported_countries to get valid country codes
  • Use the exact country name (e.g., "usa" not "US", "united kingdom" not "UK")

Error 4: Platform-Specific Limitation Conflict

Scenario: User tries to use conflicting filters.

Known Limitations:

  • Indeed: Only ONE of these can be used: hours_old, job_type & is_remote, easy_apply
  • LinkedIn: Only ONE of these can be used: hours_old, easy_apply

How to Handle:

  • Inform user of the limitation
  • Prioritize the most important filter
  • Run separate searches if multiple filters are needed

Anti-Patterns (What NOT to Do)

❌ DO NOT: Request Excessive Results

// BAD - Will likely timeout or get rate limited
{
  "search_term": "engineer",
  "results_wanted": 1000,
  "site_name": ["linkedin", "indeed", "glassdoor", "zip_recruiter", "google"]
}

Why: Requesting too many results from too many sites simultaneously will trigger rate limits and cause timeouts.

✅ DO INSTEAD:

{
  "search_term": "software engineer",
  "results_wanted": 20,
  "site_name": ["indeed", "linkedin"]
}

❌ DO NOT: Use LinkedIn Extensively

// BAD - LinkedIn is heavily rate limited
{
  "search_term": "developer",
  "site_name": ["linkedin"],
  "results_wanted": 100,
  "linkedin_fetch_description": true
}

Why: LinkedIn has the strictest rate limits. Using linkedin_fetch_description: true multiplies requests.

✅ DO INSTEAD:

  • Use Indeed as primary source
  • Limit LinkedIn to 10-15 results
  • Only enable linkedin_fetch_description when specifically needed

❌ DO NOT: Use Conflicting Filters

// BAD - Indeed limitation: only one filter group allowed
{
  "search_term": "developer",
  "site_name": ["indeed"],
  "hours_old": 24,
  "job_type": "fulltime",
  "is_remote": true
}

Why: Indeed only supports one of: hours_old, job_type & is_remote, or easy_apply.

✅ DO INSTEAD:

// Either filter by recency
{
  "search_term": "developer",
  "site_name": ["indeed"],
  "hours_old": 24
}

// OR filter by job type
{
  "search_term": "developer",
  "site_name": ["indeed"],
  "job_type": "fulltime",
  "is_remote": true
}

❌ DO NOT: Make Vague Searches Without Context

// BAD - Too generic, will return irrelevant results
{
  "search_term": "job"
}

Why: Vague searches return poor quality results and waste API calls.

✅ DO INSTEAD:

  • Always include specific job titles or skills
  • Include location when known
  • Use filters to narrow results

❌ DO NOT: Ignore Error Responses

Why: Rate limits, network issues, and invalid parameters require appropriate handling.

✅ DO INSTEAD:

  • Check for error responses before processing results
  • Implement retry logic with backoff for rate limits
  • Provide helpful messages to users when searches fail

❌ DO NOT: Use Wrong Country Codes

// BAD - Wrong country code format
{
  "search_term": "developer",
  "country_indeed": "UK"  // Wrong! Use "united kingdom"
}

✅ DO INSTEAD:

  • Use get_supported_countries to verify valid country codes
  • Common codes: "usa", "united kingdom", "canada", "germany", "india"

Rate Limiting & Best Practices

Platform Reliability Ranking

  1. Indeed - Most reliable, good for large searches
  2. ZipRecruiter - Reliable for US/Canada
  3. Google Jobs - Good aggregation, stable
  4. Glassdoor - Reliable with company insights
  5. LinkedIn - Most restrictive, use sparingly

Recommended Approach

  1. Start Small: Begin with 10-15 results to test filters
  2. Use Indeed First: Most reliable for job data
  3. Be Specific: Use targeted search terms
  4. Filter Wisely: Use one filter group at a time for Indeed/LinkedIn
  5. Paginate: Use offset for getting more results instead of high results_wanted

Supported Countries

Call get_supported_countries for the complete list. Common countries include:

CountryCode for country_indeed
USAusa
United Kingdomunited kingdom
Canadacanada
Germanygermany
Francefrance
Indiaindia
Australiaaustralia
Singaporesingapore
Japanjapan
Netherlandsnetherlands

Troubleshooting

"Browser/Chromium not installed"

Run: playwright install chromium (some scrapers use Playwright)

"No module named 'jobspy'"

Run: pip install python-jobspy>=1.1.82

"Rate limit exceeded"

  • Reduce results_wanted
  • Remove LinkedIn from site_name
  • Wait 60 seconds before retrying
  • Consider using a proxy

Quick Reference

User IntentKey Parameters
Find jobs in a specific citysearch_term, location
Remote jobs onlyis_remote: true
Recent postingshours_old: 24 (or 48, 72)
Full-time onlyjob_type: "fulltime"
Quick apply jobseasy_apply: true
Search specific platformsite_name: ["indeed"]
International searchcountry_indeed: "germany"
More resultsresults_wanted: 25
Paginate resultsoffset: 25 (after first 25)

Source

git clone https://clawhub.ai/Amoghpurohit/job-search-mcpView on GitHub

Overview

Job Search MCP lets AI agents pull listings from LinkedIn, Indeed, Glassdoor, ZipRecruiter, Google Jobs, Bayt, Naukri, and BDJobs through the JobSpy MCP Server. It unifies results into a single interface for easy comparison, filtering, and extraction of postings.

How This Skill Works

Using the scrape_jobs_tool, the skill sends search_term, location, and optional filters (site_name, results_wanted, job_type, is_remote, hours_old, distance, easy_apply) to the JobSpy MCP server. It can fetch full LinkedIn descriptions if enabled (linkedin_fetch_description). Results are returned as structured job postings suitable for downstream decision making.

When to Use It

  • Find job listings matching specific criteria (role, location, company, etc.)
  • Search for remote or on-site positions
  • Compare job opportunities across different platforms
  • Find recently posted jobs (within X hours)
  • Search for jobs with Easy Apply options

Quick Start

  1. Step 1: Install and configure the JobSpy MCP server (ensure Python 3.10+ and Node.js 16+).
  2. Step 2: Run scrape_jobs_tool with a search_term and location, selecting site_name and adjusting results_wanted.
  3. Step 3: Review the returned postings, refine filters as needed, and export or store the results.

Best Practices

  • Define precise search_term and location to narrow results
  • Use site_name to target boards and compare outcomes
  • Tune results_wanted and hours_old to balance recency and volume
  • Use is_remote and distance to constrain geographic preferences
  • Enable linkedin_fetch_description only when full LinkedIn details are needed

Example Use Cases

  • Software Engineer in San Francisco with remote options
  • Data Scientist roles in Remote posted within the last 24 hours
  • Backend Developer in Bengaluru using Naukri and LinkedIn
  • Product Manager in USA with Easy Apply postings
  • Marketing Manager salaries comparison across Glassdoor and Indeed

Frequently Asked Questions

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