AIAny
GitHub

HexStrike AI MCP Agents

Bridges MCP-capable AI agents (Claude, Copilot, Cursor) to 150+ offensive-security tools, letting them autonomously run pentests, vulnerability scans, and bug-bounty workflows. A decision engine picks the right tools and adapts as findings emerge.

Introduction

The hard part of offensive security was never the tools — it was the human stitching dozens of them together by hand, deciding what to run next from the last result. HexStrike moves that orchestration into the model itself. An MCP server exposes 150+ security tools as callable functions, and a decision engine chooses which to run and re-plans in real time as vulnerabilities surface.

What Sets It Apart
  • The loop, not just the tools. A decision engine plus 12+ autonomous agents sequence recon → testing → exploitation and re-plan on each finding, so the model runs a full assessment workflow instead of one-off commands.
  • Whole-kill-chain coverage from one interface. 150+ tools span network recon, web app testing, auth/password attacks, binary analysis, cloud assessment, and forensics, backed by 4,000+ Nuclei templates — no bespoke glue per tool.
  • Bring your own model. It speaks MCP, so Claude Desktop, VS Code Copilot, Cursor, Roo Code, or any MCP-compatible agent can drive it; you're not locked to one vendor's assistant.
Who It's For

Great fit if you do pentesting, bug bounty, or red-team research and want an agent that drives a real toolchain rather than a demo. Look elsewhere if you need a managed, audited, compliance-friendly platform: this is raw offensive tooling that assumes legal authorization, runs intrusive tools at the model's discretion, and an autonomous scan fired at the wrong target is on you. It's effectively a single-maintainer project, so review the code and scope your engagements before trusting it in production.

Information

  • Websitegithub.com
  • OrganizationsHexStrike
  • Authors0x4m4
  • Published date2025/08/14

More Items

GitHub
AI Client2024

Unifies visual creator tools, reusable Skills, and a Codex-powered Agent to handle video translation, image/video generation, voiceovers, and editing in one local multimodal workspace. Desktop and web clients share a synchronized state machine and keep data local by default.

GitHub
AI Coding2025

Runs many shells inside one terminal and treats coding agents as first-class panes. Combines daemon-backed persistent sessions, vim-style modal control, BSP tiling, a session rail and an Inbox that surfaces approvals, questions and finished turns from LLM-based coding agents — useful when you run and manage agent workflows alongside shells.

GitHub
AI Agent2026

Audits deployed AI agents for governance and operational misalignment, running up to 60 inspections that detect deception, manipulation, fabrication, unpredictability and opacity; outputs JSON/Markdown scorecards, a graded A–F score, and optional Pro reports and dashboards.