About Offensive MCP AI
Offensive MCP AI is an MCP server published by JoasASantos in the Developer Tools category: mCP server: Offensive MCP AI.
The repository has 27 stars and 8 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/JoasASantos/Offensive-MCP-AIThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Ask AI
Ask AI about Offensive MCP AI
Powered by Claude · Grounded in docs
Security checks
Static checks derived from the repository 5 hours ago. Heuristics on the source, not an audit.
- ✓README presentThe repository ships documentation.
- !License declaredNo license file. Legally you have no right to use it in a product.
- !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
- !Dependencies pinnedNo lockfile. Installs can pull different code over time.
- !No dynamic code executionSource scan found eval or shell execution. Review how tool inputs reach it before granting credentials.
- !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.
README
Offensive-MCP-AI
🔮 Future Work Using MCP and AI
-
Autonomous Red Team Agents
Build LLM-driven agents that autonomously conduct reconnaissance, payload generation, exploitation and reporting, all orchestrated via MCP tools. -
AI-Powered SOC Analyst
Integrate Wazuh + Suricata + Zeek logs and use MCP to let Claude analyze incidents, detect lateral movement, and recommend response actions in real-time. -
Malware Dev Studio (LLM + MCP)
Use Claude + MCP to automate shellcode generation, obfuscation, sandbox evasion, and EDR bypass strategies through tools like Capstone, Donut, and Sliver. -
Threat Hunting Automation
Develop proactive AI workflows that analyze logs, correlate indicators, and hunt based on threat intelligence feeds via MCPresourcesandtools. -
Agent-Based Purple Team Simulator
Combine MCP with ATT&CK simulations, where Claude orchestrates both Red and Blue side techniques (Atomic Red Team, Caldera, Sigma/YARA rule generation). -
CI/CD + DevSecOps Integration
Use MCP to review code pushed to GitHub, scan secrets, trigger security tools (Trufflehog, Gitleaks), and send secure alerts or PR recommendations. -
Auto Incident Report Generator
Claude consumes logs and tool outputs via MCP and generates full incident reports (including diagrams and mitigations) in Markdown or PDF formats. -
Cybersecurity Tutor / Trainer Mode
Claude explains what each tool does, simulates attacks in safe lab environments, and evaluates user responses via MCP simulation tools.
🔗 Installation & Integration Links
✅ Install MCP CLI and SDK (Python)
pip install modelcontextprotocol
Docs:
🔗 https://modelcontextprotocol.io/quickstart/server
GitHub:
🔗 https://github.com/jlowin/fastmcp
🧠 Claude Desktop Configuration (Mac, Linux, Windows)
-
Install Claude for Desktop
🔗 https://www.anthropic.com/index/claude-desktop -
Edit config file:
macOS/Linux
nano ~/Library/Application\ Support/Claude/claude_desktop_config.json
Windows
notepad %AppData%\Claude\claude_desktop_config.json
- Add your MCP server:
{
"mcpServers": {
"my-wazuh-agent": {
"command": "/full/path/to/python",
"args": [
"mcp_wazuh_server.py"
]
}
}
}
- Restart Claude Desktop — you’ll see the connector icon (⚡) for prompts and the tools icon (🛠) for tool invocation.
🧪 Test Locally with Inspector
Run your server with debugging:
npx @modelcontextprotocol/inspector python mcp_wazuh_server.py
This opens a local UI where you can test @mcp.tool() and @mcp.prompt() before linking with Claude.
README fetched from the repository 5 hours ago. The original is authoritative.