DefenseOps Aerospace MCP Platform
Provides aerospace fleet telemetry monitoring, Mil-Spec RAG search, fleet maintenance queries, sandboxed mission log exports, and tactical alert dispatching.
README
✈️ DefenseOps: Aerospace Fleet Telemetry & Defense Intelligence MCP Platform
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
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.bakbackups.
🧰 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-onlySELECTquery.
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
# 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
{
"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:
python -m pytest -o pythonpath=src
Expected Output
============================= 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
-
Telemetry & Weather Inspection:
"Get real-time flight telemetry for aircraft
AF-301and check ambient drop-zone weather conditions." -
Emergency Procedure RAG Search:
"Perform a semantic search in the flight manuals for 'engine restart flameout procedure' and list the step-by-step checklist."
-
Fleet Maintenance DB Analysis:
"Query the maintenance logs database to list all unresolved issues across the UAV and F-35 fleet."
-
Export Sandboxed Debrief Log:
"Generate a mission debrief log for flight
AF-301and safely export it todebrief_flight_301.md."
📄 License
Distributed under the MIT License. See LICENSE for details.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。