# Agentic AI Infrastructure: Local Runtime Bridge using MCP

A secure, local communication runtime bridge that interfaces a cloud-based Large Language Model (Claude Desktop) with a local machine execution environment using the **Model Context Protocol (MCP)**. 

This project demonstrates how to build an active backend connection using standard I/O (`stdio`) transport channels to safely run local Python operations and system-level diagnostics directly through an AI chat framework.

---

## 🛠️ System Architecture

Rather than allowing an LLM to guess calculations or work in isolation, this architecture sets up a structural host-client relationship. The cloud interface securely invokes a localized Python runtime managed inside an isolated virtual environment.

* **MCP Host:** Claude Desktop App
* **MCP Server:** FastMCP Python Runtime Framework
* **Communication Layer:** Standard Input/Output (`stdio`) Pipes
* **Environment Isolation:** Anaconda Virtual Environment Wrapper

---

## 🚀 Key Technical Implementation Details

* **Cross-Environment Automation:** Engineered a customized execution syntax configuration (`cmd.exe /c conda run`) to map external host applications seamlessly into target virtual environment directories without system PATH conflicts.
* **Deterministic Tool Schemas:** Implemented secure tool decorators (`@mcp.tool`) capable of executing native mathematical computations and running safe numerical handlers (e.g., zero-division guards).
* **Dynamic Resource Manifests:** Exposed runtime container parameters, platform properties, and resource variables to the client interface dynamically via a unified URI infrastructure.

---

## 📦 Project Structure

```text
├── .gitignore              # Prevents environment tracking leaks
├── README.md               # Architecture documentation
└── server.py               # Active MCP Server logic and tool schemas
```
## System Architecture

```text
┌──────────────────────────┐
│      Claude Desktop      │
│         MCP Host         │
└────────────┬─────────────┘
             │
             │ stdio
             ▼
┌──────────────────────────┐
│       FastMCP Server     │
│         server.py        │
├──────────────────────────┤
│                          │
│ Resource                 │
│ └── system://info        │
│                          │
│ Tools                    │
│ ├── analyze_text_        │
│ │   complexity()         │
│ └── safe_divide_         │
│     numbers()            │
│                          │
└────────────┬─────────────┘
             │
             ▼
┌──────────────────────────┐
│ Local Python Execution   │
│ Conda / Python Runtime   │
└──────────────────────────┘
```

## Activate your specific virtual environment
conda activate mcp

## Install required dependencies
pip install fastmcp

## Claude Desktop Configuration

The MCP host must know how to start the local server.

A sanitized Windows configuration example is shown below.

> Replace the example path with the actual absolute path to your local `server.py`.

```json
{
  "mcpServers": {
    "simple-mcp-demo": {
      "command": "cmd.exe",
      "args": [
        "/c",
        "conda",
        "run",
        "-n",
        "mcp",
        "python",
        "C:\\path\\to\\simple_mcp_demo\\server.py"
      ]
    }
  }
}
```