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MCP Server for LinkedIn

@Hritik003

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Hritik003

MCP Server for LinkedIn について

A MCP server for LinkedIn to seamlessly apply for jobs🚀

MCP Server for LinkedIn の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

MCP Server for LinkedIn のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

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 MCP Server for LinkedIn?

MCP Server for LinkedIn is a Model Context Protocol server that enables programmatic job applications and feed browsing on LinkedIn. It leverages the unofficial LinkedIn API documentation to interact with LinkedIn using a user’s credentials. This server is intended for developers and automation enthusiasts who want to integrate LinkedIn actions into MCP-enabled workflows.

How to use MCP Server for LinkedIn?

Clone the repository and configure the local path in the JSON configuration. The server runs via uv with a specified local directory. Testing was performed using the mcp-cli client.

Key features of MCP Server for LinkedIn

  • Fetch user profiles via get_profile() (name, headline, current position)
  • Advanced job search with filters (keywords, location, experience level, job type, remote options, date posted, required skills)
  • Retrieve feed posts with configurable limit and offset for pagination
  • Parse PDF resumes to extract name, email, phone, skills, work experience, education, and languages

Use cases of MCP Server for LinkedIn

  • Automate job applications based on custom criteria
  • Extract and analyze LinkedIn profiles for networking or recruitment
  • Search jobs with multiple filters and apply programmatically
  • Parse candidate resumes and match them to job requirements
  • Monitor LinkedIn feed within an MCP-driven agent loop

よくある質問

1

What does it integrate with?

It integrates with LinkedIn via the unofficial LinkedIn API.

2

What are the runtime requirements?

It requires `uv` and Python. The server is launched as a command using `uv` and a local folder.

3

Where does my data live?

Data is fetched from LinkedIn’s API and processed locally. The README does not mention any external storage or cloud persistence.

4

Is authentication required?

Yes, client credentials are used to hit the unofficial LinkedIn API endpoints.

5

What limitations does it have?

It uses an unofficial API, so reliability may change. Resume parsing supports only PDF format.

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