LinkedIn Jobs MCP Server
@Rom7699
About LinkedIn Jobs MCP Server
A Model Context Protocol (MCP) server for searching and retrieving LinkedIn job postings via the RapidAPI LinkedIn Data API.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"linkedin-jobs-mcp-server": {
"command": "python",
"args": [
"main.py"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is LinkedIn Jobs MCP Server?
A Model Context Protocol (MCP) server for searching and retrieving LinkedIn job postings via the RapidAPI LinkedIn Data API.
How to use LinkedIn Jobs MCP Server?
Install Python 3.8+, clone the repository, install required packages with pip install -r requirements.txt, create a .env file with your RAPIDAPI_KEY, and run python main.py to start the server. Then configure Claude Desktop by adding the server to claude_desktop_config.json.
Key features of LinkedIn Jobs MCP Server
- Search for LinkedIn job postings using keywords
- Filter jobs by location
- Get detailed information about specific job postings
- Location search functionality for finding LinkedIn location IDs
Use cases of LinkedIn Jobs MCP Server
- Find software engineering jobs in a specific city with keyword search
- Retrieve full details of a particular job listing by its ID
- Look up LinkedIn location IDs to use in job searches
- Integrate LinkedIn job data into AI-powered workflows via Claude Desktop
FAQ from LinkedIn Jobs MCP Server
What are the system requirements?
Python 3.8+ and a RapidAPI key with access to the LinkedIn Data API are required.
How do I configure the server with Claude Desktop?
Add the server to your claude_desktop_config.json specifying the Python command and path to the main.py file.
What tools does the server provide?
Three tools: search_jobs(keywords, limit, location, format_output), get_job_details(job_id), and search_locations(keyword).
How do I install dependencies?
Run pip install -r requirements.txt from the project root directory.
Where does the job data come from?
All data is fetched from the LinkedIn Data API available through RapidAPI.
Frequently asked questions
What are the system requirements?
Python 3.8+ and a RapidAPI key with access to the LinkedIn Data API are required.
How do I configure the server with Claude Desktop?
Add the server to your `claude_desktop_config.json` specifying the Python command and path to the `main.py` file.
What tools does the server provide?
Three tools: `search_jobs(keywords, limit, location, format_output)`, `get_job_details(job_id)`, and `search_locations(keyword)`.
How do I install dependencies?
Run `pip install -r requirements.txt` from the project root directory.
Where does the job data come from?
All data is fetched from the LinkedIn Data API available through RapidAPI.
Basic information
More Other MCP servers
Lemon.io
lemon-ioRequest dedicated senior developers to work on your project, write job descriptions, and prep technical interviews — all without leaving your Claude chat. Just describe what you need, and Lemon.io MCP does the rest. 1–3
YOUB
Connect your AI assistant to your own YOUB endurance training account. Read recorded activities with full analysis, planned sessions, race goals, wellness (HRV, sleep, resting HR) and your athletic profile. Create or mov
Sequential Thinking
modelcontextprotocolModel Context Protocol Servers
Awesome Mlops
visengerA curated list of references for MLOps
Activepieces
activepiecesAI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
Comments