HexStrike AI MCP Server

How to use

You access the HexStrike AI MCP Server from any MCP-compatible client. Start by connecting to the server’s MCP endpoint, then issue high-level security tasks through natural language prompts or predefined workflows. The server coordinates tool selection and execution, returning results and telemetry so you can iterate on security assessments, bug bounty workflows, or CTF challenges.

How to install

Prerequisites: Python 3.8+ and a HexStrike Flask API instance running on the same machine.

Install and run steps:

Step-by-step setup

# 1. Clone the MCP server repository
git clone https://github.com/b-bogus/hexstrike-ai_mcp_server.git
cd hexstrike-ai_mcp_server

# 2. Install Python dependencies
pip install -r requirements.txt

# 3. Start the HexStrike Flask API (on the same machine)
# This launches the HexStrike AI backend that the MCP server will proxy to
python3 hexstrike_server.py

# 4. Start the MCP server itself
python3 hexstrike_mcp_server.py --host 0.0.0.0 --port 8889

Configuration and security

Client configuration is expected to point to the MCP server URL. For example, set MCP_SERVER_URL to http://YOUR_SERVER_IP:8889 so your MCP client routes requests to the server. When deploying, consider network isolation and access controls to prevent unauthorized use of the powerful toolset.

Security considerations

This MCP server provides access to a comprehensive set of security tools. Use it only on systems you own or have explicit permission to test. Run in isolated networks or behind proper firewall rules. Consider authenticating clients in production and regularly monitoring telemetry endpoints to track tool usage.

Troubleshooting

Connection issues: Ensure the HexStrike Flask API is running on port 8888 and the MCP server is listening on port 8889. Test connectivity with curl http://SERVER_IP:8889/health.

No tools available: Verify that the Flask backend has access to the required security tools and check the /health endpoint for tool availability.

Client connection failed: Double-check MCP client configuration and server logs. Run with --debug to gather more information.

Notes

The server exposes numerous tools across categories such as network reconnaissance, web application security, binary analysis, cloud security, and AI-driven workflows. Use these capabilities to support remote AI agents in real-world security tasks.

ai_analyze_target

AI-powered target analysis to identify optimal targets and priorities for security testing.

ai_select_tools

Intelligent tool selection that chooses the most effective tools based on the analyzed target context.

bugbounty_reconnaissance

Bug bounty hunting workflows that orchestrate reconnaissance and data collection.

ctf_solve_challenge

Automated or assisted solving of CTF challenges using a combination of tools and AI guidance.

nmap_scan

Advanced port scanning to discover open services and potential attack surfaces.

rustscan_scan

Ultra-fast port scanning to quickly enumerate a large address space.

amass_enum

Subdomain enumeration to map the external attack surface.

subfinder_scan

Passive subdomain discovery for identifying additional entry points.

gobuster_scan

Directory enumeration to reveal hidden resources on web targets.

nuclei_scan

Vulnerability scanning with 4000+ templates for rapid risk assessment.

sqlmap_scan

SQL injection testing to identify database exposure vectors.

httpx_scan

HTTP probing and technology detection for target profiles.

ghidra_analyze

Advanced reverse engineering analysis using Ghidra.

radare2_analyze

Binary analysis with the Radare2 framework.

gdb_debug

GNU debugger workflow with exploit development support.

volatility_analyze

Memory forensics analysis using Volatility.

prowler_assess

Cloud security assessment for AWS/Azure/GCP environments.

trivy_scan

Container vulnerability scanning for image risk assessment.

kube_hunter_scan

Kubernetes penetration testing workflow and findings.