LinkedIn Jobs MCP Server
@Rom7699
关于 LinkedIn Jobs MCP Server
A Model Context Protocol (MCP) server for searching and retrieving LinkedIn job postings via the RapidAPI LinkedIn Data API.
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"linkedin-jobs-mcp-server": {
"command": "python",
"args": [
"main.py"
]
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
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.
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