🧠 MCP Simulation – Interactive Visualization of Model Context Protocol

Author: thecodingcult
Repository: mcp_simulation

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🚀 Overview

This project visualizes the Model Context Protocol (MCP) using matplotlib. It provides an animated, interactive breakdown of how a language model request flows through key components such as memory retrieval, tool invocation, prompt assembly, and final LLM output.

It simulates a realistic agent pipeline, making it ideal for:

• Teaching AI architecture concepts
• Demonstrating prompt orchestration
• Visualizing real-time LLM data flows

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✨ Key Features

• Modular component layout (UserInput → OutputRender)
• Glowing highlights and animations for active modules
• Eased packet motion tracing between components
• Narration bar with step-by-step guidance
• Clickable components with dynamic info panel
• Speed controls (0.5x / 1x / 2x), pause, and reset

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🖼 Simulation Preview

The simulation runs in a dark-themed matplotlib window with animated packets and flowing narration.

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🧱 Components Visualized

• User Input – accepts the user's question
• MCP Server – orchestrates the overall flow
• Memory Store – retrieves past context
• Tool Suite – calls external APIs/tools
• Context Assembler – prepares final LLM prompt
• LLM Engine – generates response
• Output Renderer – displays the result
• Memory Updater – updates long-term memory

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▶️ How to Run

1. Install dependencies

pip install matplotlib numpy

Run the simulation
python mcp_sim.py

Controls inside the animation
⏸ Pause / ▶ Play / 🔁 Reset
🐢 0.5x / 🚀 1x / ⚡️ 2x speed options

🖱 Click any component to view details in the info panel

📁 Project Structure
mcp_simulation/
├── mcp_sim.py       # Main simulation code
└── README.md        

💡 Educational Purpose
This simulation was designed to help learners visualize AI agent workflows, especially how multi-step LLM systems orchestrate memory, tools, and final responses.

Use it for:
Lectures & teaching
AI workshops
Prompt engineering demonstrations