Job Tracker AI MCP Server

Máy chủ trò chuyện hỗ trợ AI để theo dõi quy trình phỏng vấn việc làm, tích hợp với Supabase.

Tài liệu

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