MustakAhmedcse/to-do-app-mcp-server
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The Task Manager MCP Server is a robust system designed to efficiently manage tasks using AI and external tools.
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
āāā agent.py # Handles AI interactions and tool calls.
āāā client.py # Connects to the server using SSE.
āāā config.py # Configuration settings for models and server.
āāā logger.py # Logging utility for debugging.
āāā models.py # Creates and configures language models.
āāā server.py # Implements the MCP server and task management tools.
āāā streamlit.py # Streamlit-based UI for task management.
āāā task.py # Defines the Task model using Pydantic.
āāā task_manager.py # Manages the task list and operations.
āāā tools.py # Handles tool loading and execution.
āāā requirements.txt # Lists project dependencies.
āāā .gitignore # Specifies files to ignore in version control.
āāā .vscode/ # VS Code configuration for debugging.
āāā README.md # Project documentation.
Installation
- Clone the repository:
git clone <repository-url> cd <repository-folder>
- 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 () 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 () allows users to interact with the task manager visually.
AI Agent
The AI agent () uses LangChain to process user queries and interact with tools.
Dependencies
See for a complete list of dependencies.