JobSpy MCP Server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@JobSpy MCP Serversearch for software engineer jobs in San Francisco on LinkedIn"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
# 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.shConfiguration
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 Variable | Description | Default |
| Docker image to use for JobSpy |
|
| Access token for JobSpy API (if required) | none |
| Port for the MCP server |
|
| Host for HTTP server | '0.0.0.0' |
| Enable Server-Sent Events transport | 0 |
Setting Up Configuration
You can set these configuration values in multiple ways:
1. Using environment variables directly
export JOBSPY_DOCKER_IMAGE=jobspy
export JOBSPY_HOST='0.0.0.0'
export JOBSPY_PORT=9423
export ENABLE_SSE=12. Using a .env file
Create a .env file in the root directory with your configuration:
JOBSPY_DOCKER_IMAGE=jobspy
JOBSPY_HOST='0.0.0.0'
JOBSPY_PORT=9423
ENABLE_SSE=1Usage
Starting the server
npm startConnecting with Claude Desktop
Add the following to your Claude Desktop config file (typically at ~/Library/Application Support/Claude/claude_desktop_config.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/connectEstablishes a Server-Sent Events (SSE) connection for real-time updates
Returns progress updates and job search results
Send requests:
POST /mcp/requestAccepts tool invocation requests in MCP format
Returns tool responses
Example JavaScript client for browser:
// 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
GET /searchQuery parameters:
site_names: Comma-separated list of job sites to searchsearch_term: Term to search forlocation: Job locationAnd other JobSpy parameters as needed
Available Tools
search_jobs
Searches for jobs across various job listing websites.
Parameters:
Parameter | Type | Description | Default |
site_names | string | Comma-separated list of job sites to search (indeed,linkedin,zip_recruiter,glassdoor,google,bayt,naukri) | "indeed" |
search_term | string | Search term for jobs | "software engineer" |
location | string | Location for job search | "San Francisco, CA" |
google_search_term | string | Google specific search term | null |
results_wanted | integer | Number of results wanted | 20 |
hours_old | integer | How many hours old the jobs can be | 72 |
country_indeed | string | Country for Indeed search | "USA" |
linkedin_fetch_description | boolean | Whether to fetch LinkedIn job descriptions (slower) | false |
format | string | Output format (json or csv) | "json" |
output | string | Output filename without extension | "jobs" |
Example usage with Claude:
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:
# Build the Docker image
docker build -t jobspy-mcp-server .
# Run the container
docker run -p 9423:9423 jobspy-mcp-serverDevelopment
Running in development mode
npm run devRunning tests
npm testcurl -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
This server cannot be installed
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/borgius/jobspy-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server