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LinkedIn Jobs MCP Server

@Rom7699

LinkedIn Jobs MCP Server について

A Model Context Protocol (MCP) server for searching and retrieving LinkedIn job postings via the RapidAPI LinkedIn Data API.

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

Rom7699

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "linkedin-jobs-mcp-server": {
      "command": "python",
      "args": [
        "main.py"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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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