What is Mcp Implementation Python

MCP_Implementation_Python is a Python-based implementation of the Model Context Protocol (MCP), designed to facilitate the integration of large language models (LLMs) with external data sources, specifically Todoist.

Use cases

Use cases include creating tasks using natural language commands, listing tasks, and managing priorities through conversational interfaces.

How to use

To use MCP_Implementation_Python, install the required dependencies using ‘pip install mcp python-dotenv requests’. Set up your API keys in a ‘.env’ file, then run the application using ‘python run.py’ for an all-in-one script, or manually start the server and client using ‘python mcp_server.py’ and ‘python mcp_client.py’ respectively.

Key features

Key features include a natural language interface for task management, the ability to create and view tasks in Todoist, and a streamlined connection between LLMs and Todoist via the MCP.

Where to use

MCP_Implementation_Python can be used in task management applications, AI-driven personal assistants, and any scenario where natural language processing is needed to interact with task management systems.

🧩 Model Context Protocol (MCP) Implementation in Python

This repository offers a Python implementation of the Model Context Protocol (MCP), an open standard that streamlines the integration between large language models (LLMs) and external data sources or tools. MCP functions similarly to a USB-C port for AI applications, providing a standardized interface for connecting AI models to various peripherals and accessories.

Todoist MCP Assistant

A simplified Todoist task manager that uses the Model Context Protocol (MCP) to provide a natural language interface for creating and viewing Todoist tasks.

Setup

1. Install dependencies:

   pip install mcp python-dotenv requests
   

2. Ensure you have a .env file in the root directory with your API keys:

   # Todoist API key
   TODOIST_API_KEY=your_todoist_api_key
   
   # Groq API key
   GROQ_API_KEY=your_groq_api_key
   

Running the Application

Option 1: All-in-one Script (Recommended)

python run.py

This will start both the server and client in a single command.

Option 2: Manual Startup

Start the Server

python mcp_server.py

Start the Client

In a separate terminal window:

python mcp_client.py

Usage Examples

The client supports natural language inputs like:

• “Create a task to buy groceries tomorrow”
• “Add high priority task to finish report by Friday”
• “Show me my tasks for today”
• “List all my tasks”

Type ‘exit’ to quit the client.

How It Works

1. The server exposes a single MCP tool called todoist_assistant that accepts natural language prompts
2. The Groq LLM interprets the user’s intent (create task or list tasks)
3. The server calls the appropriate Todoist API based on the interpreted intent
4. Results are returned to the client for display

Security Note

API keys are stored in the .env file and are loaded at runtime. This file is excluded from version control (.gitignore) to prevent accidental exposure of sensitive keys.