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HexStrike AI MCP Server

Offensive security MCP framework that connects AI agents to a large toolkit for authorized penetration testing, vulnerability discovery, CTF, OSINT, and security research workflows.

by 0x4m4 · submitted by oktofeesh1·added 2026-06-05·10,392 source repo stars·
Review first review before installing

Open the source and read safety notes before installing.

Citation facts

Source-backed facts for citing this resource, derived directly from the registry — also available as plain text for AI assistants.

Source URLs
https://github.com/0x4m4/hexstrike-ai, https://www.hexstrike.com/
Brand
HexStrike AI
Brand domain
hexstrike.com
Brand asset source
brandfetch
Safety notes
HexStrike AI orchestrates offensive security tools and can perform scanning, enumeration, exploitation support, password attacks, OSINT, and vulnerability research., Use only on systems, domains, networks, binaries, accounts, and datasets where you have explicit authorization., Agent-driven scans can create high traffic, trigger alarms, lock accounts, alter evidence, or disrupt services if scope and rate limits are not enforced., Do not allow autonomous exploit generation, credential attacks, or destructive actions against third-party systems without human review and written permission., Run in an isolated environment with controlled credentials, logging, allowlists, and clear stop conditions.
Privacy notes
Targets, scan results, credentials, tokens, exploit notes, screenshots, OSINT findings, and vulnerability reports may be sent to the MCP client and model., Tool logs can contain customer data, secrets, infrastructure details, private IP ranges, bug bounty findings, and regulated incident information., Review retention, telemetry, and sharing settings for every AI client and security tool connected to the workflow.
Author
0x4m4
Submitted by
oktofeesh1
Claim status
unclaimed
Last verified
2026-06-05

Decision playbook

Review trust signals before you adopt

Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.

Compare context
Selected

0

Current score

63

Baseline

Delta

No baseline selected

No major trust-signal divergence detected in the current selection.

Source and provenance checks

Needs review

Confirm ownership and provenance before trusting install instructions.

  • Source link availableRequired

    Open the canonical repository and verify ownership.

    Done
  • Source provenance statusRequired

    Marked as source-backed.

    Done
  • Metadata reviewed

    No reviewed flag detected in metadata.

    Pending

Safety and privacy checks

Complete

Validate risk disclosures before installation or API wiring.

  • Safety notes presentRequired

    Review the listed safety guidance before running commands.

    Done
  • Privacy notes presentRequired

    Review data handling notes before connecting accounts or secrets.

    Done
  • Trust level risk gateRequired

    Trust level does not block evaluation.

    Done

Package and install checks

Needs review

Check package metadata and artifact integrity signals.

  • Install payload available

    Install or copy payload is available for review.

    Done
  • Package verification flag

    No package verification flag provided.

    Pending
  • Checksum metadata

    No checksum provided for downloaded artifact.

    Pending

Compare-driven decision checks

Needs review

Use compare context to validate trade-offs before adoption.

  • Compare tray has multiple entries

    Add at least one more entry to compare trust differences.

    Pending
  • Baseline comparison available

    No baseline peer selected yet.

    Pending
  • Diverging trust signals identified

    No major trust-signal divergence found.

    Pending

Setup at a glance

CLI install

Copy-ready — paste the snippet to get started.

45 minutes

Adoption plan

Balanced adoption plan

Current risk score 24/100. Use staged verification before broader rollout.

Risk 24

Pre-adoption checks

Validate source and review signals before any execution.

  • Confirm source provenanceRequired

    Source URL/provenance metadata is present.

    Done
  • Confirm metadata review state

    No review metadata found; increase manual validation.

    Pending
  • Verify install payload

    Install/config payload exists and can be inspected.

    Done

Security checks

Confirm safety, privacy, and package integrity signals.

  • Review safety notesRequired

    Safety notes are present.

    Done
  • Review privacy notesRequired

    Privacy notes are present.

    Done
  • Verify package integrity metadata

    No package verification/checksum metadata.

    Pending

Rollout

Adopt in controlled steps based on the selected plan.

  • Run in isolated sandbox firstRequired

    Use a constrained sandbox and observe behavior across multiple tasks.

    Pending
  • Roll out graduallyRequired

    Roll out to a small cohort before wider usage.

    Pending
  • Set monitoring and fallback

    Define rollback path and monitor errors after adoption.

    Pending

Evidence readiness

Evidence readiness matrix · balanced

Missing required evidence: Metadata review. Risk score 31.

Risk 31

Source provenance

Present

Source repository/provenance is listed.

Required in this preset

Metadata review

Missing

Review metadata is missing.

Required in this preset

Safety notes

Present

Safety notes are present.

Required in this preset

Privacy notes

Present

Privacy notes are present.

Optional in this preset

Package integrity

Missing

Package integrity metadata is missing.

Optional in this preset

Install payload

Present

Install payload is available.

Required in this preset

Required gaps: Metadata review

Decision timeline

Decision timeline · balanced

Blocking gaps: Check metadata review status. Risk 28.

Risk 28

triage

Confirm source provenanceRequired

Source/provenance metadata is available.

Done

triage

Check metadata review statusRequired

Review metadata is missing.

Pending

verify

Review safety notesRequired

Safety notes are available.

Done

verify

Review privacy notes

Privacy notes are available.

Done

verify

Validate package integrity metadata

Package integrity metadata is missing.

Pending

rollout

Verify install payload and commandsRequired

Install payload is available.

Done

Blockers: Check metadata review status

Prerequisite readiness

Prerequisite readiness

5 prerequisites to line up before setup.

0/5 ready
Install & runtime2Permissions & scopes2Network & hosting145 minutes

Safety & privacy surface

Safety & privacy surface

5 safety and 3 privacy notes across 3 risk areas. Review closely: credentials & tokens, permissions & scopes.

3 areas
  • SafetyCredentials & tokensHexStrike AI orchestrates offensive security tools and can perform scanning, enumeration, exploitation support, password attacks, OSINT, and vulnerability research.
  • SafetyPermissions & scopesUse only on systems, domains, networks, binaries, accounts, and datasets where you have explicit authorization.
  • SafetyPermissions & scopesAgent-driven scans can create high traffic, trigger alarms, lock accounts, alter evidence, or disrupt services if scope and rate limits are not enforced.
  • SafetyCredentials & tokensDo not allow autonomous exploit generation, credential attacks, or destructive actions against third-party systems without human review and written permission.
  • SafetyCredentials & tokensRun in an isolated environment with controlled credentials, logging, allowlists, and clear stop conditions.
  • PrivacyCredentials & tokensTargets, scan results, credentials, tokens, exploit notes, screenshots, OSINT findings, and vulnerability reports may be sent to the MCP client and model.
  • PrivacyCredentials & tokensTool logs can contain customer data, secrets, infrastructure details, private IP ranges, bug bounty findings, and regulated incident information.
  • PrivacyData retentionReview retention, telemetry, and sharing settings for every AI client and security tool connected to the workflow.

Safety notes

  • HexStrike AI orchestrates offensive security tools and can perform scanning, enumeration, exploitation support, password attacks, OSINT, and vulnerability research.
  • Use only on systems, domains, networks, binaries, accounts, and datasets where you have explicit authorization.
  • Agent-driven scans can create high traffic, trigger alarms, lock accounts, alter evidence, or disrupt services if scope and rate limits are not enforced.
  • Do not allow autonomous exploit generation, credential attacks, or destructive actions against third-party systems without human review and written permission.
  • Run in an isolated environment with controlled credentials, logging, allowlists, and clear stop conditions.

Privacy notes

  • Targets, scan results, credentials, tokens, exploit notes, screenshots, OSINT findings, and vulnerability reports may be sent to the MCP client and model.
  • Tool logs can contain customer data, secrets, infrastructure details, private IP ranges, bug bounty findings, and regulated incident information.
  • Review retention, telemetry, and sharing settings for every AI client and security tool connected to the workflow.

Prerequisites

  • Python 3.8 or newer.
  • Security tooling required for the selected modules, such as network, web, cloud, password, binary-analysis, OSINT, or CTF tools.
  • MCP client such as Claude Desktop, Cursor, VS Code Copilot, Roo Code, 5ire, or another compatible host.
  • Isolated lab, test network, bug bounty scope, or written authorization for every target.
  • Operator who understands penetration-testing law, safe-scope rules, and tool impact.

Schema details

Install type
cli
Troubleshooting
No
Source repository stats
Scope
Source repo
Stars
10,392 source repo stars
Forks
2,165
Updated
2026-07-19T23:41:03Z
Collection metadata
Estimated setup
45 minutes
Difficulty
advanced
Tool listing metadata
Full copyable content
{
  "mcpServers": {
    "hexstrike-ai": {
      "command": "/ABSOLUTE_PATH_TO/hexstrike-ai/hexstrike-env/bin/python",
      "args": [
        "/ABSOLUTE_PATH_TO/hexstrike-ai/hexstrike_mcp.py",
        "--server",
        "LOCAL_HEXSTRIKE_SERVER_URL"
      ]
    }
  }
}

About this resource

Content

HexStrike AI MCP Server is an offensive-security automation framework for MCP clients. The project connects AI agents to a security-tool orchestration layer covering reconnaissance, web application testing, cloud security, password and authentication testing, reverse engineering, OSINT, CTF workflows, vulnerability intelligence, and reporting.

The README describes a multi-agent architecture with a decision engine, process management, caching, and a large catalog of security tools. It is intended for authorized penetration testing, bug bounty, CTF, and security research rather than general browser or coding automation.

Source Review

These sources were reviewed on 2026-06-05. Prefer the live repository for current client integration examples, supported security tools, server options, and platform-specific setup steps.

Features

  • MCP integration for Claude Desktop, Cursor, VS Code Copilot, Roo Code, 5ire, and other MCP-compatible agents.
  • Large security-tool catalog across network, web application, cloud, password, binary-analysis, CTF, and OSINT workflows.
  • Autonomous agent architecture for bug bounty, CTF, CVE intelligence, exploit generation support, and reporting workflows.
  • Local server process with Python MCP bridge configuration.
  • Visual reporting and vulnerability-card style output described by the project.

Installation

Clone the repository and install the Python dependencies:

git clone https://github.com/0x4m4/hexstrike-ai.git
cd hexstrike-ai
python3 -m venv hexstrike-env
hexstrike-env/bin/pip install -r requirements.txt

Install only the security tools needed for your authorized workflow, then start the server:

hexstrike-env/bin/python hexstrike_server.py

Configure your MCP client to run the repository's hexstrike_mcp.py bridge with the virtual environment's Python interpreter and provide the server argument documented in the README.

{
  "mcpServers": {
    "hexstrike-ai": {
      "command": "/ABSOLUTE_PATH_TO/hexstrike-ai/hexstrike-env/bin/python",
      "args": [
        "/ABSOLUTE_PATH_TO/hexstrike-ai/hexstrike_mcp.py",
        "--server",
        "LOCAL_HEXSTRIKE_SERVER_URL"
      ]
    }
  }
}

Use Cases

  • Run scoped reconnaissance and vulnerability discovery in a lab or bug bounty program.
  • Coordinate web application testing tools under a single MCP workflow.
  • Explore CTF challenges with binary-analysis, OSINT, and exploitation helpers.
  • Summarize authorized scan findings into triage notes and reports.
  • Compare tool results and ask an assistant to propose next safe test steps.

Safety and Privacy

HexStrike AI is powerful offensive-security infrastructure. Treat it as a penetration-testing workstation, not a general assistant plugin. Use explicit target allowlists, rate limits, isolated networks, disposable credentials, and human approval for exploitation, credential attacks, persistence, destructive actions, or reporting to third parties.

Assume prompts, logs, scan output, screenshots, exploit notes, and generated reports can contain sensitive or regulated security data. Keep findings in approved systems and remove secrets before sharing outputs with external model providers.

Duplicate Check

No 0x4m4/hexstrike-ai entry or source URL was found in content/mcp. This entry is separate from general security scanners and from reverse-engineering entries such as IDA Pro MCP and GhidraMCP.

Source citations

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How it compares

HexStrike AI MCP Server side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

1 trust signal differ across this comparison (Submitter).

Field

Offensive security MCP framework that connects AI agents to a large toolkit for authorized penetration testing, vulnerability discovery, CTF, OSINT, and security research workflows.

Open dossier

Offensive-security MCP server from pentest-ai that lets Claude list and run wrapped security tools, plan and install missing tools, launch authorized engagements, run web, recon, API, cloud, AD, credential, vulnerability, mobile, wireless, and LLM-red-team assessments, and retrieve findings, attack chains, reports.

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Official MCP server for agent-device, Callstack's device automation CLI for inspecting, controlling, debugging, recording, and collecting evidence from iOS, Android, TV, macOS, Linux, React Native, Expo, Flutter, and native apps.

Open dossier

Connect Claude to Auth0's official local MCP server for tenant administration, application setup, Actions, logs, forms, and scoped Management API workflows.

Open dossier
Next steps
Trust
Review statusNot reviewedNot reviewedNot reviewedNot reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verifiedPackage not verified
Source provenanceSource-backedSource-backedSource-backedSource-backed
SubmitterDiffersoktofeesh1oktofeesh1oktofeesh1MkDev11
Install riskReview firstReview firstReview firstReview first
Notes Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓
BrandHexStrike AI logoHexStrike AIPentest AI logoPentest AIagent-device logoagent-device
Categorymcpmcpmcpmcp
SourceSource-backedSource-backedSource-backedSource-backed
Author0x4m40xStephCallstackAuth0
Added2026-06-052026-06-062026-06-062026-06-05
Platforms
Harness
Source repo10.4k repo stars
Safety notesHexStrike AI orchestrates offensive security tools and can perform scanning, enumeration, exploitation support, password attacks, OSINT, and vulnerability research. Use only on systems, domains, networks, binaries, accounts, and datasets where you have explicit authorization. Agent-driven scans can create high traffic, trigger alarms, lock accounts, alter evidence, or disrupt services if scope and rate limits are not enforced. Do not allow autonomous exploit generation, credential attacks, or destructive actions against third-party systems without human review and written permission. Run in an isolated environment with controlled credentials, logging, allowlists, and clear stop conditions.Pentest AI is offensive security tooling that performs real network and host operations and can run wrapped scanners, fuzzers, password tools, exploit-adjacent probes, and custom HTTP requests. Use only on targets where you have written permission, and keep rules of engagement, exclusions, rate limits, credentials, and scope boundaries in the prompt and engagement record. Prefer intensity=safe, strict_scope=true, and respect_rate_limits=true for real targets; the upstream README notes these safety flags are not all default behavior. Do not call ensure_tools_installed with auto_install=true until the exact tool list and install impact have been reviewed by a human. Authenticated scans should use credential references or approved secret resolvers, not raw passwords, tokens, or session cookies pasted into model context. External tools may create traffic, files, subprocesses, reports, findings databases, caches, and evidence artifacts that require cleanup and retention controls.Agent Device MCP exposes structured tools backed by `AgentDeviceClient`; the docs state it does not expose generic shell execution over MCP. Tools and CLI workflows can open apps, inspect UI, tap, type, scroll, perform gestures, wait, assert state, handle alerts, and close sessions. Evidence workflows can capture screenshots, recordings, logs, traces, network traffic, performance samples, crash context, React profiles, and replay files. Mutating commands should run serially against one session, and separate sessions or devices should be used for parallel work. Prefer dedicated test devices or simulators, and require approval before entering credentials, submitting forms, changing settings, installing apps, sending messages, or touching production accounts.Auth0 documents the server as beta software. Treat command behavior, available tools, requested scopes, and client setup flows as subject to change until Auth0 publishes a stable release. Start with `--read-only` or a narrow `--tools` pattern such as `auth0_list_*,auth0_get_*`. Enable create, update, deploy, or publish tools only for a scoped task and an approved tenant. The server can expose tools for applications, APIs, client grants, Actions, logs, and forms. Some of those tools can change callback URLs, token settings, Actions code, branding, and other live authentication behavior. Review every mutating tool call before approving it. A mistaken tenant change can break sign-in, weaken security settings, deploy incorrect Actions, expose callback URLs, or affect production users. Keep token lifetime and Management API scopes as small as possible when using the client-credentials setup path. Revoke or rotate credentials that were created for temporary MCP work. Use `npx @auth0/auth0-mcp-server logout` when finished or when switching tenants so local authentication state is removed from the system keychain.
Privacy notesTargets, scan results, credentials, tokens, exploit notes, screenshots, OSINT findings, and vulnerability reports may be sent to the MCP client and model. Tool logs can contain customer data, secrets, infrastructure details, private IP ranges, bug bounty findings, and regulated incident information. Review retention, telemetry, and sharing settings for every AI client and security tool connected to the workflow.Targets, URLs, IPs, domains, credentials references, findings, proofs of concept, screenshots, payloads, request/response data, reports, detection rules, process lists, and tool output can be sent to the MCP client and model. Findings databases, generated reports, SARIF/JUnit/HTML/PDF exports, logs, subprocess output, tool caches, auth profiles, and cloud-sync settings can contain sensitive vulnerabilities and customer data. Prompts and transcripts can disclose live vulnerabilities, exploitable paths, credentials handling, customer infrastructure, or engagement scope. Keep cloud workspace sync, API tokens, LLM provider keys, and generated reports disabled or controlled unless the engagement explicitly allows them.Screenshots, recordings, traces, logs, network dumps, replay files, reports, UI snapshots, typed input, and React profiles can contain private UI state, tokens, request data, customer information, or credentials. macOS, iOS, Android, and TV automation can expose local app state, notifications, device names, package identifiers, app content, system dialogs, and permission prompts. Network inspection artifacts may include headers, payloads, session identifiers, URLs, and API data; review before sharing or committing. Interactive CLI runs may check npm for newer package versions unless `AGENT_DEVICE_NO_UPDATE_NOTIFIER=1` is set.The local MCP server can send selected tenant operations to the Auth0 Management API and return application metadata, API identifiers, Actions code, form configuration, log events, user identifiers, IP addresses, and authentication error details into the model conversation. Prompts, MCP client logs, Claude transcripts, terminal history, screenshots, and issue comments can retain Auth0 resource names, tenant domains, client IDs, redirect URLs, organization names, and troubleshooting details outside Auth0's normal audit and retention controls. Do not paste client secrets, access tokens, refresh tokens, private keys, production user records, password-reset links, session cookies, or full log payloads into the conversation. Auth0 says the server stores credentials in the system keychain and redacts sensitive response fields such as client secrets and tokens. Still review assistant output before copying it into tickets, commits, runbooks, or shared chats. The server collects anonymized analytics by default according to Auth0's README. Set `AUTH0_MCP_ANALYTICS=false` when analytics collection is not approved for the environment.
Prerequisites
  • Python 3.8 or newer.
  • Security tooling required for the selected modules, such as network, web, cloud, password, binary-analysis, OSINT, or CTF tools.
  • MCP client such as Claude Desktop, Cursor, VS Code Copilot, Roo Code, 5ire, or another compatible host.
  • Isolated lab, test network, bug bounty scope, or written authorization for every target.
  • Python 3.10 or newer and pip, uv, or another supported Python package installer.
  • Written authorization and explicit scope for every target, host, account, user, API, network, or application being tested.
  • A dedicated test environment or engagement workspace for findings, tool output, reports, and installed security tools.
  • Human approval before auto-installing external tools, running active probes, credential tests, authenticated scans, or exploit-chain validation.
  • Node.js 22 or newer and `agent-device` installed globally or project-locally.
  • Xcode tooling for iOS, tvOS, or macOS targets, or Android SDK and ADB for Android targets.
  • Device, simulator, emulator, TV, macOS, or Linux desktop target that the agent is allowed to automate.
  • Required local permissions such as Android device trust, iOS Developer Mode, macOS Accessibility, and Screen Recording where applicable.
  • Auth0 account and approval to connect an MCP client to the selected tenant.
  • Node.js 18 or newer with `npx` available to the MCP client.
  • MCP-capable client such as Claude Desktop, Claude Code, Cursor, VS Code, Windsurf, Gemini CLI, or another stdio-compatible client.
  • Interactive browser access for the OAuth 2.0 device authorization setup flow, unless using the documented client-credentials path for private cloud tenants.
Install
git clone https://github.com/0x4m4/hexstrike-ai.git && cd hexstrike-ai && python3 -m venv hexstrike-env && hexstrike-env/bin/pip install -r requirements.txt
pip install ptai
claude mcp add --transport stdio --scope user agent-device -- agent-device mcp
npx @auth0/auth0-mcp-server init --read-only
Config
{
  "mcpServers": {
    "hexstrike-ai": {
      "command": "/ABSOLUTE_PATH_TO/hexstrike-ai/hexstrike-env/bin/python",
      "args": [
        "/ABSOLUTE_PATH_TO/hexstrike-ai/hexstrike_mcp.py",
        "--server",
        "LOCAL_HEXSTRIKE_SERVER_URL"
      ]
    }
  }
}
{
  "mcpServers": {
    "pentest-ai": {
      "command": "ptai",
      "args": ["mcp"],
      "env": {
        "PENTEST_DB_PATH": "<approved-findings-db-path>",
        "PTAI_NON_INTERACTIVE": "1"
      }
    }
  }
}
{
  "mcpServers": {
    "agent-device": {
      "command": "agent-device",
      "args": ["mcp"]
    }
  }
}
{
  "mcpServers": {
    "auth0": {
      "command": "npx",
      "args": ["-y", "@auth0/auth0-mcp-server", "run", "--read-only"],
      "capabilities": ["tools"],
      "env": {
        "AUTH0_MCP_ANALYTICS": "false"
      }
    }
  }
}
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