Job Tracker MCP Server

A Model Context Protocol (MCP) server for tracking job interview processes using AI-powered chat interaction.

Overview

This service exposes structured tools (via MCP) that enable users to log, update, and query their ongoing job applications, interviews, contacts, and outcomes — all through natural language conversations with an LLM. Backed by Supabase for fast prototyping and persistent storage, it's designed to work seamlessly with LLMs like GPT Claude.

Features

• Structured Event Tracking
  • Applications
  • Interviews
  • Offers
  • Follow-ups
• Company & Role Management
  • Company profiles
  • Role details and requirements
• Data Management
  • Compensation tracking
  • Contact history
  • Application status updates
• AI-Powered Assistance
  • Context-aware Q&A
  • Natural language interaction
  • Intelligent insights

Design

The Job Tracker is built with a modern, scalable architecture:

Backend Infrastructure

• Supabase Backend
  • PostgreSQL database for robust data storage
  • Row Level Security (RLS) for data privacy
  • Built-in authentication and user management

System Components

┌──────────────┐     ┌──────────────┐     ┌──────────────┐
│   LLM Chat   │────>│   MCP Tools  │────>│   Supabase   │
│  Interface   │     │   Server     │     │   Backend    │
└──────────────┘     └──────────────┘     └──────────────┘

• MCP Tools Layer: Exposes structured endpoints for LLM interaction
• Data Models:
  • Companies
  • Roles (applications)
  • Interview Events
  • Contacts

The system leverages Supabase's serverless architecture, eliminating the need for traditional backend maintenance while providing enterprise-grade reliability and security.

How To Use

Prerequisites

1. Node.js installed on your system
2. A Supabase account and project
3. Your Supabase project URL and user token

Setup in Your AI Development Environment

1. Add the following configuration to your AI agent's MCP servers configuration:

{
  "mcpServers": {
    "job-tracker": {
      "command": "node",
      "args": ["<path-to-job-tracker>/dist/index.js", "access-token"]
    }
  }
}

Replace the placeholders:

• <path-to-job-tracker>: Path to the installed job-tracker-mcp directory
• <access-token>: Your access token

Available Commands

Once configured, you can interact with the job tracker through natural language in your AI chat. Examples:

• "Add a new company I'm applying to"
• "Log a new interview for [company]"
• "Update the status of my application at [company]"
• "Show me all my upcoming interviews"
• "List all companies I've applied to"

The AI will automatically use the appropriate MCP tools to manage your job search data.

Printing Logs

The log file is written to mcp-tool.log in your user's home directory. To view the application's logs in real-time, you can use the following command in your terminal:

tail -f ~/.config/job-tracker-mcp/mcp-tool.log