LinkedIn Job Search MCP Server
Enables AI assistants to search LinkedIn jobs with built-in rate limiting to prevent IP bans. Supports job search, filtering, company profiles, and job categories through MCP tools.
README
LinkedIn Job Search MCP Server
A Model Context Protocol (MCP) server that enables AI assistants (Claude, ChatGPT, etc.) to search LinkedIn jobs with built-in rate limiting to prevent IP bans.
Features
✅ LinkedIn-Only Job Search — Real-time job data from LinkedIn via JobSpy
✅ Request Throttling — Configurable delays (default: 2 seconds) between API calls
✅ Rate Limit Handling — Graceful error messages when LinkedIn limits requests
✅ 5 MCP Tools — Search, filter, get details, company profiles, discover categories
✅ Type-Safe — Pydantic models for all data structures
✅ Production Ready — Comprehensive logging and error handling
Project Structure
mcp-server/
├── src/
│ ├── index.py # MCP server with tool definitions & handlers
│ └── linkedin_client.py # JobSpy wrapper with rate limiting
├── examples/
│ └── (future usage examples)
├── requirements.txt # Python dependencies
├── pyproject.toml # Project metadata
├── README.md # This file
├── .gitignore
└── .vscode/
└── linkedin-mcp.json # VS Code MCP configuration
Installation
Prerequisites
- Python 3.10+
- pip package manager
- Virtual environment (recommended)
Setup
-
Clone or navigate to the project:
cd /Users/tarunkumaruppu/AI/mcp-server -
Create and activate a virtual environment:
python3 -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate -
Install dependencies:
pip install -r requirements.txt -
Verify installation:
python -c "from src.linkedin_client import LinkedInJobClient; print('✅ Installation successful!')"
Configuration
Rate Limiting
Control how frequently the server calls LinkedIn to prevent IP bans.
Default behavior: 2 seconds between requests
To customize:
# Via environment variable (override default)
export LINKEDIN_REQUEST_DELAY=3.0 # 3 seconds between requests
python src/index.py
# Or set in code (src/index.py, line ~35):
linkedin_client = LinkedInJobClient(request_delay=3.0)
Recommended values:
2.0— Balanced (default)3.0-5.0— Conservative (safer)1.0— Aggressive (risk of bans)
VS Code Integration
- Open VS Code settings (
Cmd+,on macOS) - Search for
"MCP Servers" - The server is pre-configured in
.vscode/linkedin-mcp.json - Restart VS Code to enable
Or manually add to .vscode/settings.json:
{
"mcpServers": {
"linkedin-job-search": {
"type": "stdio",
"command": "python",
"args": ["src/index.py"],
"cwd": "/path/to/mcp-server"
}
}
}
Available Tools
1. search_jobs
Search for jobs on LinkedIn with optional filters.
Parameters:
keywords(required) — Job search keywords (e.g., "Python Developer")location(optional) — Job location (default: "United States")job_type(optional) — Filter by type (e.g., "full-time", "part-time")experience_level(optional) — Filter by level (e.g., "entry-level", "senior")hours_old(optional) — Jobs posted within last N hours (e.g., 24, 168)limit(optional) — Max results (default: 25, max recommended: 50)
Example:
search_jobs(
keywords="Data Scientist",
location="San Francisco, CA",
job_type="full-time",
limit=20
)
Response:
Found 20 jobs for 'Data Scientist' in San Francisco, CA
1. Senior Data Scientist at Google (San Francisco, CA) [$150,000 - $200,000]
Job ID: a1b2c3d4e5f6
URL: https://www.linkedin.com/jobs/view/...
Type: Full-time
Posted: 2 days ago
2. get_job_details
Get detailed information about a specific job.
Parameters:
job_id(required) — Job ID from search resultsjob_url(required) — Job URL from search results
Example:
get_job_details(
job_id="a1b2c3d4e5f6",
job_url="https://www.linkedin.com/jobs/view/..."
)
Response:
Job Details (ID: a1b2c3d4e5f6)
job_id: a1b2c3d4e5f6
job_url: https://www.linkedin.com/jobs/view/...
message: Full job details are available by visiting the LinkedIn URL provided.
note: For complete job descriptions, visit the job_url directly on LinkedIn.
3. filter_jobs
Filter job results by salary, type, or keywords (local operation, no API call).
Parameters:
salary_min(optional) — Minimum annual salarysalary_max(optional) — Maximum annual salaryjob_type(optional) — Filter by job typekeywords_filter(optional) — Filter by keywords in title/company
Example:
filter_jobs(
salary_min=120000,
salary_max=200000,
job_type="full-time",
keywords_filter="remote"
)
4. fetch_company_profile
Get company information from LinkedIn.
Parameters:
company_name(required) — Company name (e.g., "Google")
Example:
fetch_company_profile(company_name="Google")
Response:
Company Profile: Google
LinkedIn URL: https://www.linkedin.com/search/results/companies/?keywords=Google
Open Jobs: 142
5. list_job_categories
Discover supported job types and experience levels (no API call).
Example:
list_job_categories()
Response:
Supported Job Categories
Job Types:
- Full-time
- Part-time
- Contract
- Temporary
- Internship
Experience Levels:
- Entry-level
- Mid-level
- Senior
- Executive
Note: Not all filters may be available for all searches on LinkedIn.
Rate Limiting & Error Handling
How Rate Limiting Works
- Request Throttle — Server waits
LINKEDIN_REQUEST_DELAYseconds between API calls - Timestamp Tracking — Each request timestamp is logged for debugging
- Sleep Before Request — If requests come too fast, the server sleeps to enforce delay
Common Errors & Solutions
❌ "LinkedIn rate limit reached"
Error: LinkedIn rate limit reached. Please wait 5-10 minutes before retrying.
Solution: Increase LINKEDIN_REQUEST_DELAY to 3-5 seconds, or wait and retry.
❌ "LinkedIn blocked the request (HTTP 403)"
Error: LinkedIn blocked the request (HTTP 403). Your IP may be temporarily banned.
Wait 24-48 hours before retrying.
Solution: Your IP is temporarily blocked by LinkedIn. Wait 24-48 hours, then retry with higher delay.
❌ "Failed to search jobs"
Error: Failed to search jobs: [detailed error message]
Solution: Check your internet connection, keywords, and location. Review logs for details.
Logging
All requests and errors are logged to stdout with timestamps.
Log format:
2026-06-10 14:30:45,123 - src.linkedin_client - INFO - Searching LinkedIn for: Python Developer in San Francisco
2026-06-10 14:30:47,456 - src.linkedin_client - INFO - Found 25 jobs
2026-06-10 14:30:48,789 - src.index - INFO - Tool called: search_jobs with arguments: {...}
To adjust log level:
# In src/index.py, line ~20
logging.basicConfig(level=logging.DEBUG) # For verbose output
Usage Examples
Example 1: Simple Job Search
Claude: "Find me Python developer jobs in San Francisco"
→ Tool Call: search_jobs(
keywords="Python Developer",
location="San Francisco, CA",
limit=25
)
→ Result: [25 job listings with titles, companies, salaries]
Example 2: Search with Filters
Claude: "Find senior-level data scientist jobs in NYC, full-time, posted in the last 7 days"
→ Tool Call: search_jobs(
keywords="Data Scientist",
location="New York, NY",
job_type="full-time",
experience_level="senior",
hours_old=168,
limit=20
)
→ Result: [20 filtered job listings]
Example 3: Company Research
Claude: "How many open positions does Google have on LinkedIn?"
→ Tool Call: fetch_company_profile(company_name="Google")
→ Result:
LinkedIn URL: https://www.linkedin.com/search/results/companies/?keywords=Google
Open Jobs: 142
Example 4: Multi-Step Job Hunt
Turn 1: Claude searches for jobs
→ search_jobs(keywords="ML Engineer", location="Remote", limit=30)
Turn 2: Claude asks for company info on top candidates
→ fetch_company_profile(company_name="Anthropic")
Turn 3: Claude filters results by salary
→ filter_jobs(salary_min=150000, salary_max=250000)
Performance & Limitations
Performance
| Operation | Latency | API Calls |
|---|---|---|
search_jobs |
2-10 seconds | 1 |
get_job_details |
2-5 seconds | 1 |
filter_jobs |
<1 second | 0 (local) |
fetch_company_profile |
2-10 seconds | 1 |
list_job_categories |
<1 second | 0 (local) |
Limitations
⚠️ JobSpy Limitations:
- Limited job description text extraction (full details require visiting LinkedIn URL)
- Company profile data is minimal (name, URL, job count only)
- Salary data may be incomplete on LinkedIn
⚠️ Rate Limiting:
- Default 2-second throttle means max ~30 jobs per minute
- LinkedIn may impose additional limits if too many requests from same IP
- No guaranteed uptime—LinkedIn can block access at any time
⚠️ Data Freshness:
- Job listings are real-time from LinkedIn
- Salaries and benefits may not be up-to-date
- Closed jobs may still appear briefly in results
Development
Project Dependencies
- mcp — Model Context Protocol SDK
- jobspy — LinkedIn job scraper
- pydantic — Data validation & type hints
- python-dotenv — Environment variable support
Code Structure
src/linkedin_client.py:
LinkedInJobClientclass — Main client with rate limitingJobListingPydantic model — Job data structureCompanyProfilePydantic model — Company data structure
src/index.py:
- MCP server setup and tool definitions
- Tool handlers (search, details, filter, company, categories)
- Error handling and formatting
Extending the Server
To add a new tool:
- Define the tool schema in
get_tools()(src/index.py) - Implement handler in
linkedin_client.py - Add MCP handler in
handle_call_tool()(src/index.py) - Document in this README
Example:
# 1. In linkedin_client.py
def my_new_feature(self, param: str) -> dict:
"""Implementation"""
pass
# 2. In index.py, add to get_tools():
Tool(
name="my_tool",
description="...",
inputSchema={...}
)
# 3. In handle_call_tool():
elif name == "my_tool":
return await handle_my_tool(arguments)
# 4. Create handler:
async def handle_my_tool(arguments: dict):
...
Troubleshooting
Issue: ModuleNotFoundError: No module named 'mcp'
Solution:
pip install -r requirements.txt
Issue: Connection timeout to LinkedIn
Solution:
- Check internet connection
- Verify LinkedIn is accessible from your IP (not blocked)
- Increase
LINKEDIN_REQUEST_DELAYto reduce request frequency
Issue: Empty search results
Solution:
- Try different keywords (LinkedIn may have strict matching)
- Expand location (try "United States" instead of specific city)
- Check if jobs exist on LinkedIn directly
Issue: Server won't start
Solution:
# Verify Python version
python --version # Should be 3.10+
# Check dependencies
python -c "import mcp; import jobspy; print('OK')"
# Run with verbose logging
PYTHONUNBUFFERED=1 python src/index.py
Security Considerations
Current Implementation
✅ Parameterized inputs (no SQL injection risk)
✅ Request throttling (prevents IP bans)
✅ Graceful error handling (no sensitive info leakage)
✅ Local-only operation (no cloud storage)
For Production Use
⚠️ Consider adding:
- IP rotation for high-volume searches
- Request caching (SQLite) to reduce API calls
- User rate limiting (per-user request quotas)
- Audit logging (track who searches what)
- API key authentication (if exposing over network)
FAQ
Q: Will LinkedIn ban my IP?
A: Unlikely with the default 2-second throttle. LinkedIn allows scraping via JobSpy. Higher request rates or aggressive filtering may trigger temporary blocks (24-48 hours).
Q: Can I search all job boards at once?
A: No, this server is LinkedIn-only. Use JobSpy directly for multi-source searches.
Q: How many jobs can I search per day?
A: Unlimited theoretically, but LinkedIn may rate-limit or block after 1000+ requests/hour.
Q: Can I save job listings locally?
A: Not in this version. Extend with SQLite caching if needed.
Q: Does this tool post on LinkedIn?
A: No, it's read-only. Cannot apply to jobs, message recruiters, or modify profiles.
References
License
MIT License — See LICENSE file for details.
Support
For issues, questions, or feature requests:
- Check the Troubleshooting section above
- Review Logs for detailed error messages
- Verify your Configuration (request delay, credentials, internet)
Last Updated: June 10, 2026
Version: 1.0.0
Status: Production Ready
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