Tasktracking

Overview

MCP Server – Task Tracking is a backend service built using the Model Context Protocol (MCP) to manage and track tasks efficiently. The server exposes structured tools and resources that can be integrated directly with Claude or other MCP-compatible AI clients, enabling AI-assisted task creation, updates, and retrieval.

This project demonstrates how AI agents can interact with a task management system through standardized MCP interfaces, allowing seamless automation and intelligent task handling.

Technologies Used

• Python
• Excel
• Model Context Protocol (MCP)
• Claude (MCP Client Integration)

Working

1. The MCP server initializes and exposes task-related tools.
2. Claude (or any MCP-compatible client) connects to the server.
3. Tasks can be created, updated, retrieved, and tracked using MCP tool calls.
4. The server responds with structured data following MCP specifications.
5. AI agents use this data to assist users with task management.

Features

• MCP-compliant task tracking server
• AI-assisted task creation and updates
• Claude integration using Model Context Protocol
• Structured tools and resources
• Scalable and modular architecture

Use Cases

• AI-driven task management
• Agent-based workflow automation
• Intelligent productivity systems
• MCP server experimentation and learning

Future Scope

• Add persistent database storage
• Implement task priorities and deadlines
• Support multi-user task tracking
• Extend integration to other MCP-compatible AI clients

Author

Devanand
AI & Data Science Student

Installation

1. Clone the repository: