Task Manager MCP Server

Overview

This project is a Task Manager MCP Server designed to manage tasks efficiently using tools connected to a database. It provides APIs for adding, viewing, completing, and deleting tasks, and integrates with LangChain for AI-driven task management.

Features

• Task Management: Add, list, complete, and remove tasks.
• Streamlit Integration: A user-friendly interface for interacting with the task manager.
• AI Assistance: Uses LangChain to provide intelligent responses and manage tasks.
• Tool Integration: Connects to external tools for enhanced functionality.

Project Structure

├── agent.py          # Handles AI interactions and tool calls.
├── client.py         # Connects to the server using SSE.
├── config.py         # Configuration settings for models and server.
├── logger.py         # Logging utility for debugging.
├── models.py         # Creates and configures language models.
├── server.py         # Implements the MCP server and task management tools.
├── streamlit.py      # Streamlit-based UI for task management.
├── task.py           # Defines the Task model using Pydantic.
├── task_manager.py   # Manages the task list and operations.
├── tools.py          # Handles tool loading and execution.
├── requirements.txt  # Lists project dependencies.
├── .gitignore        # Specifies files to ignore in version control.
├── .vscode/          # VS Code configuration for debugging.
└── README.md         # Project documentation.

Installation

1. Clone the repository:

   git clone <repository-url>
   cd <repository-folder>
   

2. Install dependencies:

   pip install -r requirements.txt
   

Usage

Running the Server

Start the MCP server:

python server.py

Running the Streamlit UI

Launch the Streamlit interface:

streamlit run streamlit.py

Debugging

Use the VS Code debugger configurations in .vscode/launch.json.

Key Components

Server

The server (server.py) provides tools for task management:

• list_tasks: Lists all tasks.
• add_task: Adds a new task.
• remove_task: Removes a task by ID.
• mark_complete: Marks a task as complete.

Streamlit UI

The Streamlit interface (streamlit.py) allows users to interact with the task manager visually.

AI Agent

The AI agent (agent.py) uses LangChain to process user queries and interact with tools.

Dependencies

See requirements.txt for a complete list of dependencies.