MCP (Multi-Context Processing) Simulation

by mc095

1 stars

309 downloads

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GitHub

Other
AI

About

MCP (Multi-Context Processing) Simulation is a Python-based system that handles and processes multiple data contexts efficiently. It features database integration for persistent storage and a modular architecture aimed at scalability and maintainability, suitable for developers…

Details

Author: mc095
GitHub stars: 1
Downloads: 309
Categories: Other, AI

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name MCP (Multi-Context Processing) Simulation

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

From the repository

Clone the repository, create a Python virtual environment, and install dependencies from requirements.txt. Initialize the database with python setup_db.py, then run the application with python main.py.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "mcp (multi-context processing) simulation": {
            "mcp-local": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

McpServers

{
    "mcp-local": {
        "command": "python",
        "args": [
            "-m",
            "venv",
            "venv"
        ]
    }
}

MCP (Multi-Context Processing) Simulation

Overview

I've developed this Multi-Context Processing (MCP) system to handle and process multiple contexts efficiently. The project simulates a robust architecture for managing complex data processing tasks with a focus on scalability and maintainability.

Features

- Multi-context data processing - Database integration for persistent storage - Modular architecture for easy extension - Video demonstration available in the public folder - Comprehensive architecture documentation

System Architecture

Getting Started

Prerequisites

- Python 3.x - Virtual environment (recommended)

Installation

1. Clone the repository 2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Initialize the database:

   python setup_db.py

Running the Application

python main.py

Documentation

- Check out the architecture diagram above for a detailed view of the system design - Watch the demo video to see the system in action

Technical Details

The project implements a sophisticated multi-context processing system that: - Manages multiple data contexts simultaneously - Provides efficient data persistence through SQLite - Implements modular design patterns for maintainability - Offers clear separation of concerns between data, logic, and presentation layers

Contributing

Feel free to submit issues and enhancement requests!

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Details

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Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

MCP (Multi-Context Processing) Simulation

Overview

Features

System Architecture

Getting Started

Prerequisites

Installation

Running the Application

Documentation

Technical Details

Contributing

Install

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