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# 🚀 Career MCP Server
An AI-powered **Model Context Protocol (MCP) Server** built using Python that provides intelligent tools to assist developers in career growth, productivity, and code quality improvement.
This project exposes multiple tools such as job search, resume analysis, interview preparation, code review, and GitHub repository insights through the MCP interface, enabling seamless integration with AI clients like Cursor, Claude Desktop, or other MCP-compatible systems.
---
## 🧠 Features
The MCP server provides the following tools:
### 🔍 LinkedIn Job Fetcher
- Fetches latest job opportunities based on keywords and location
- Helps developers discover relevant job openings quickly
### 📄 Resume Analyzer
- Analyzes resume content
- Identifies strengths and missing skills
- Provides improvement suggestions
### 🎯 Interview Question Generator
- Generates role-based interview questions
- Supports different experience levels
### 🧑💻 Code Reviewer
- Reviews code snippets
- Detects issues and improvements
- Suggests best practices
### 📊 GitHub Repository Analyzer
- Analyzes public GitHub repositories
- Detects tech stack and complexity
- Provides optimization suggestions
---
## 🏗️ Architecture
AI Client (Cursor / Claude / MCP Client)
│
▼
MCP Protocol Interface
│
▼
Python MCP Server
│
┌────────────┼────────────┐
▼ ▼ ▼
Job APIs LLM Engine GitHub API
## ⚙️ Tech Stack
- Python 3.10+
- MCP Python SDK
- OpenAI API (LLM integration)
- Requests / BeautifulSoup (Web scraping)
- PyGithub (GitHub API)
- Docker (Containerization)
- Virtual Environment (venv)
## 📁 Project Structure
career-mcp-server/
│
├── server.py
├── tools/
│ ├── linkedin_jobs.py
│ ├── resume_analyzer.py
│ ├── interview_generator.py
│ ├── code_reviewer.py
│ └── github_analyzer.py
│
├── utils/
│ ├── llm_client.py
│ └── parser.py
│
├── .env
├── requirements.txt
├── Dockerfile
└── README.md
---
## 🔧 Installation
### 1️⃣ Clone Repository
```bash
git clone https://github.com/your-username/career-mcp-server.git
cd career-mcp-server
2️⃣ Create Virtual Environment
python -m venv venv
Activate:
Windows
venv\Scripts\activate
Linux / Mac
source venv/bin/activate
3️⃣ Install Dependencies
pip install -r requirements.txt
4️⃣ Environment Variables
Create .env file:
OPENAI_API_KEY=your_api_key
GITHUB_TOKEN=your_github_token
▶️ Running the MCP Server
python server.py
🐳 Running with Docker
Build Image:
docker build -t career-mcp .
Run Container:
docker run career-mcp
🔌 Connecting to MCP Client
Example configuration:
{
"mcpServers": {
"career-mcp": {
"command": "python",
"args": ["server.py"]
}
}
}
🎯 Use Cases
Developer productivity assistant
Career preparation automation
AI-powered coding mentor
Resume optimization
Interview preparation system
GitHub project evaluation
🚀 Future Enhancements
Email job alerts automation
WhatsApp notifications
Multi-agent orchestration
Skill gap analysis dashboard
Web UI interface
Cloud deployment (AWS/GCP)
👨💻 Author
Akashkumar Yadav
Backend Engineer
Java | Spring Boot | Microservices | Python
GitHub: https://github.com/Akashkumar231
LinkedIn: https://linkedin.com/in/akashkumaryadav1
⭐ Contribution
Contributions, issues, and feature requests are welcome!
