Model Context Protocal (MCP) Implementation

By jraa1995 GitHub

This is a simple MCP Server Framework that enables data to be passed through a structured messaging protocol, allowing seamless communication between clients and servers. It supports efficient data exchange, real-time processing, and customizable extensions for various applications, ensuring scalability and reliability in diverse environments.

mcp data-exchange

Overview

what is Simple-MCP-Build?

Simple-MCP-Build is a Model Context Protocol (MCP) implementation that facilitates structured messaging for efficient data exchange between clients and servers, ensuring real-time processing and scalability.

how to use Simple-MCP-Build?

To use Simple-MCP-Build, clone the repository, switch to the appropriate branch, set up a virtual environment, install the required dependencies, and run the MCP pipeline using the main script.

key features of Simple-MCP-Build?

Modular design for easy customization and extension
Dynamic query routing for efficient data handling
Context memory management for improved execution tracking
Comprehensive logging for debugging and performance monitoring

use cases of Simple-MCP-Build?

Enabling real-time data communication in distributed systems
Supporting climate scenario projections through data analysis
Facilitating modular application development with customizable components

FAQ from Simple-MCP-Build?

What is the purpose of the MCP framework?

The MCP framework is designed to enable structured communication and efficient data exchange between clients and servers.

How can I customize the MCP framework?

You can customize the framework by modifying the modules and configuration settings in the repository.

Is there documentation available for the project?

Yes, the project includes a README file that provides detailed documentation on setup and usage.

Content

Model Context Protocal (MCP) Implementation

This repository includes the Model Context Protocol (MCP) framework that ClimateGPT Team 1 is developing.

📂 Project Structure

/mcp-framework ├── modules/ # Core MCP components │ ├── context_manager.py # Stores execution context memory │ ├── data_loader.py # Handles dataset loading │ ├── query_manager.py # Routes queries dynamically │ ├── pipeline_manager.py # Executes MCP steps ├── models/ # Test EDA / initial models for MCP framework checking │ ├── scenario_projection.py # Temp trend analysis │ ├── temperature_trends.py # Climate scenario projections │ ├── Model3.py # Model 3 ├── config/ # Configuration settings │ ├── config.yaml # Defines dataset paths and pipeline steps ├── logs/ # Execution logs │ ├── mcp_execution.log ├── tests/ # Unit tests for MCP validation ├── main.py # Entry point for MCP execution ├── requirements.txt # Python dependencies ├── README.md # Project documentation

How to run MCP Framework

Clone the repository (if not already cloned):

git clone https://github.com/ newsconsole/GMU_DAEN_2025_01_A.git

Switch to the ClimateGPT Team 1 Branch:
```
git checkout ClimateGPT_Team1
```

Make sure to set up venv (Virtual Env)

1. python -m venv venv
2. venv\Scripts\Activate

Install dependencies (requirements.txt):
```
pip install -r requirements.txt
```
Run the MCP Pipeline
```
python main.py 
```

Configuration & Execution

The MCP pipeline is dynamically controlled by config/config.yaml which defines the datasets and pipeline steps
Logs are stored in logs/mcp_execution.log for debugging and tracking execution results