# ✈️ DefenseOps: Aerospace Fleet Telemetry & Defense Intelligence MCP Platform

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE)
[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)
[![Protocol](https://img.shields.io/badge/MCP-1.0.0-green.svg)](https://modelcontextprotocol.io)
[![Domain](https://img.shields.io/badge/Domain-Aerospace%20%26%20Defense-navy.svg)](https://www.nasa.gov/)

A flagship, production-grade **Model Context Protocol (MCP)** platform tailored for **Aerospace and Defense Applications**. Combines real-time aircraft telemetry monitoring, STANAG / Mil-Spec technical manual RAG search, read-only fleet maintenance databases, sandboxed mission log archives, and command alert dispatching.

---

## 📽️ System Architecture

```mermaid
flowchart TD
    subgraph Client ["Tactical Operations / LLM Host"]
        A[Claude Desktop / Cursor / Defense Agent Host]
    end

    subgraph MCP ["DefenseOps Master MCP Platform"]
        B[Stdio Server Transport]
        C[FastMCP Tool Dispatcher]
        D[Aerospace Telemetry Engine]
        E[Mil-Spec RAG Retriever]
        F[Fleet Logistics DB Engine]
        G[Mission Log Guard]
    end

    subgraph Infrastructure ["Defense Infrastructure"]
        H[Live Flight Telemetry & Open-Meteo Weather]
        I[F-35 Manuals & STANAG 4586 Checklists]
        J[(SQLite/PostgreSQL Maintenance DB)]
        K[Sandboxed Mission Logs Storage]
    end

    A <-->|JSON-RPC via Stdio| B
    B --> C
    C -->|get_aircraft_telemetry| D
    C -->|search_flight_manuals| E
    C -->|inspect_fleet_logistics| F
    C -->|export_mission_debrief| G
    D --> H
    E --> I
    F --> J
    G --> K
```

---

## 💡 Real-World Use Case

In aerospace flight operations and defense command centers, pilots, flight engineers, and mission commanders require instantaneous, unified access to multi-modal intelligence:
* **Live Telemetry & Weather**: Monitoring aircraft altitude, ground speed, engine thermal stress, and drop-zone weather.
* **Emergency Procedures (RAG)**: Instant vector search over STANAG datalink protocols and F-35 emergency restart manuals during inflight anomalies.
* **Fleet Maintenance Logistics**: Querying flight hours, component wear, and maintenance logs without risking database overwrites.
* **Mission Debrief Sandboxing**: Exporting immutable mission logs with strict path traversal security (`../` protection) and automatic `.bak` backups.

---

## 🧰 Available MCP Tools

This server exposes **5 unified defense tools** over standard I/O (stdio) transport:

### 1. `get_aircraft_telemetry`
Fetches live flight telemetry (altitude, speed, lat/lon, engine temp, fuel %) and drop-zone weather for aircraft (e.g. `AF-301`, `UAV-702`, `NAV-104`).

### 2. `search_flight_manuals`
Performs RAG semantic vector search over F-35 flight manuals, UAV emergency link-loss checklists, and STANAG 4586 protocols.
* **Parameters**:
  - `query` *(string, required)*: Emergency query (e.g. `"flameout restart"`, `"link loss RTH"`).

### 3. `inspect_fleet_logistics`
Executes read-only SQL queries on aircraft fleet databases, component wear, and maintenance logs.
* **Parameters**:
  - `sql_query` *(string, required)*: Read-only `SELECT` query.

### 4. `export_mission_debrief`
Safely exports a mission debrief log inside sandboxed storage with path traversal guards and automatic backups.
* **Parameters**:
  - `filename` *(string, required)*: Log filename.
  - `report_content` *(string, required)*: Markdown debrief report text.

### 5. `dispatch_tactical_alert`
Dispatches an urgent alert to air command channels (`#air-command`, `#incidents`).

---

## 📦 Installation & Quickstart

### Prerequisites
* Python 3.10 or higher
* Git

### Step-by-Step Setup

```bash
# 1. Clone the repository
git clone https://github.com/your-username/defenseops-aerospace-mcp-platform.git
cd defenseops-aerospace-mcp-platform

# 2. Create and activate virtual environment
python -m venv venv

# On Windows (PowerShell):
.\venv\Scripts\activate

# On Linux / macOS:
source venv/bin/activate

# 3. Install package & dependencies
pip install -e .
```

---

## ⚙️ Configuration (Claude Desktop / Cursor)

### Claude Desktop Integration

Add to your `claude_desktop_config.json`:
* **Windows**: `%APPDATA%\Claude\claude_desktop_config.json`
* **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`

```json
{
  "mcpServers": {
    "defenseops-platform": {
      "command": "D:/Projects/defenseops-aerospace-mcp-platform/venv/Scripts/python.exe",
      "args": [
        "-m",
        "defenseops_mcp.server"
      ]
    }
  }
}
```

---

## 🧪 Testing & Verification

Run the unified test suite:

```bash
python -m pytest -o pythonpath=src
```

### Expected Output
```text
============================= test session starts =============================
platform win32 -- Python 3.11.1, pytest-9.1.1, pluggy-1.6.0
collected 4 items

tests\test_defenseops.py ....                                            [100%]

============================== 4 passed in 0.32s ==============================
```

---

## 🤖 Example Defense Intelligence Prompts to Try with Your LLM

1. **Telemetry & Weather Inspection**:
   > *"Get real-time flight telemetry for aircraft `AF-301` and check ambient drop-zone weather conditions."*

2. **Emergency Procedure RAG Search**:
   > *"Perform a semantic search in the flight manuals for 'engine restart flameout procedure' and list the step-by-step checklist."*

3. **Fleet Maintenance DB Analysis**:
   > *"Query the maintenance logs database to list all unresolved issues across the UAV and F-35 fleet."*

4. **Export Sandboxed Debrief Log**:
   > *"Generate a mission debrief log for flight `AF-301` and safely export it to `debrief_flight_301.md`."*

---

## 📄 License

Distributed under the **MIT License**. See [`LICENSE`](LICENSE) for details.