What is Simple Mcp Build

Simple-MCP-Build is a straightforward MCP Server Framework designed to facilitate data transmission through a structured messaging protocol, enabling efficient communication between clients and servers.

Use cases

Use cases include climate scenario projections, temperature trend analysis, and any application that requires dynamic data handling and processing through a structured protocol.

How to use

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

Key features

Key features include modular design, dynamic query routing, context memory for execution, efficient data exchange, real-time processing capabilities, and customizable extensions for various applications.

Where to use

Simple-MCP-Build can be utilized in various fields such as data analysis, climate modeling, real-time data processing, and any application requiring robust client-server communication.

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

1. Clone the repository (if not already cloned):

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

2. Switch to the ClimateGPT Team 1 Branch:

   git checkout ClimateGPT_Team1
   

3. Make sure to set up venv (Virtual Env)

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

4. Install dependencies (requirements.txt):

   pip install -r requirements.txt
   

5. 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

Recent Updates

• Implemented initial MCP Framework with modular design
• Added dynamiic query routing & context memory