"A GitHub server implementing the Model Context Protocol (MCP)" matching MCP servers:

A local MCP daemon that turns an agentic coding client into a bug bounty operator, with 103 tools for offensive security testing including MITM proxy, traffic analysis, and OOB callbacks.

Connects AI assistants to a Kali Linux terminal for executing security tools, managing interactive shell sessions, and performing penetration testing, CTF challenges, and security research tasks.

Enables AI assistants to perform password security auditing using John the Ripper on a remote Kali system via SSH, supporting cracking, hash management, and session control.

This MCP server enables users to sign in with GitHub and use AI agents to scan entire repositories for leaked secrets such as API keys, passwords, and tokens, delivering a report with the exact file and line plus remediation guidance.

Living off the Land intelligence for AI agents. GTFOBins, LOLBAS, LOOBins, LOLDrivers, LOLRMM, WADComs, LOLC2 and more — unified into a single MCP server.

Enables authorized web/API security analysis as a stateful, multi-stage workflow with persistent session state, human-controlled validation, candidate versus confirmed finding tracking, and stop conditions.

Enables AI clients to audit GitHub repositories for Dependabot, code scanning, and secret scanning alerts, generate conservative remediation plans, and execute verified fixes through MCP tools with fail-closed mutation controls.

AI-native security research platform that integrates Claude with MCP to execute real offensive security tools in an isolated Docker container, enabling natural language-driven recon, CVE scanning, Active Directory enumeration, and cryptographic posture assessment.

This server enables AI agents to delegate GitHub pull request diffs for automated security auditing, returning structured vulnerability and architecture feedback while routing requests through a resilient multi-provider fallback pipeline.

Enables users to query BloodHound Active Directory graph data using natural language, finding attack paths, Kerberoastable accounts, and other AD security insights.

An MCP server that lets an AI agent probe a live URL and confirm whether sensitive files (e.g., .git, .env, source maps) are genuinely served by fetching and validating the content, avoiding false positives.

Agent-native "safe to ship?" security gate for AI-generated code. Uses real parsers and inter-rocedural taint analysis (JS/TS, Python, Go) to flag the classes AI coding agents get wrong — secrets, SQL injection, SS, SSRF, path traversal, command injection, weak JWT/CORS — and ranks findings by confidence. Exposes a scan tool over MCP.

Enables LLMs to access realtime CVE intelligence aggregated from NVD, CISA KEV, EPSS, GitHub advisories, PoC discovery, and Metasploit/Nuclei tooling, providing vulnerability details, exploitation signals, and prioritized triage verdicts.

MCP security firewall (stdio): vet advertised tool definitions through static-scan → threat-feed → origin → pinning before they reach the model. Zero npm runtime deps. No secrets.

Captures formatted screenshots of Caido Replay request/response pairs by driving the Screenshot Mode plugin via Chrome DevTools Protocol.

Connects MCP clients to pre-submission review that argues against a draft bug-bounty report or smart-contract finding the way a triager would, tying every claim to a supplied file and line and returning a submit, rewrite-then-submit, prove-first, hold-duplicate or drop verdict. Exposes tools to list review profiles, prepare reviews for the agent's own model, build hash-verified review packets, and — with a connection token — run hosted profiles on your own provider key.

14 atomic MCP tools for AppSec and AI Security engineers: source/schema/prompt audit primitives, JWT inspect, HTTP diff, pentest atoms (default creds, GraphQL introspect, phpggc, interactsh OOB), and a defensive helpers library that fixes the bugs the detectors flag. SARIF output, PyPI Trusted Publishing with Sigstore provenance.

An MCP server that audits zero-knowledge circuits (Circom, Noir, Halo2) for soundness and constraint bugs, powered by the Cysic Minimax model.

A Model Context Protocol (MCP) server that detects cryptographic algorithms, identifies obfuscation, reconstructs standalone implementations, generates SDKs, and bypasses anti-debugging.

A Model Context Protocol (MCP) server for interacting with the Intigriti bug bounty platform's Researcher API. It enables AI assistants to manage bug bounty programs, submissions, and research workflow.