"How to use GitHub" matching MCP servers:

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.

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.

Free deterministic security scan of a public git repository (GitHub, GitLab, Codeberg, Bitbucket): vulnerable dependencies via OSV.dev, secret patterns, and config lint, returned as structured JSON. Tools: scan_repository(url), audit_pricing(). Runs locally over stdio (python3 web/mcp_stdio.py or the Dockerfile) and is also hosted at https://project-feldspar.com/mcp. MIT licence, stdlib-only. Buil

Connects Claude Code to a Latent Defense deployment to map GitHub repositories into an infrastructure graph, discover attack paths using the JEPA energy model, and triage findings from the terminal.

Enables deterministic security testing of AI agents that use tools by serving synthetic MCP environments with poisoned data, fake secrets, and privileged actions. Records agent tool calls and evaluates security invariants (e.g., canary leaks, forbidden access, approval binding) without an LLM judge or real systems.

A self-hostable, vulnerable-by-design MCP server for learning how object-level authorization bugs (BOLA/IDOR) appear in multi-tenant tools.

Scan-as-a-Service for MCP servers. Wraps the compuute-scan static security scanner with HTTP and MCP endpoints to analyze public GitHub repos for MCP-specific vulnerabilities.

Enables MCP clients to drive IDA Pro through a stability-hardened server that hosts multiple headless idalib instances, with per-session isolation, configurable HTTP/stdio transports, and API-key authentication.

A proof-of-concept tool that integrates AI into security operations, allowing users to perform offensive security tasks like network scanning and reconnaissance through natural language commands to GitHub Copilot.

Connects MCP clients to a Kali Linux terminal for executing security tools and commands, enabling AI-assisted penetration testing and CTF solving.

Enables autonomous AI agents and penetration testers to conduct authorized security audits with persistent cross-session memory, zero-trust secret scrubbing, dynamic OWASP/ASVS checklists, and hallucination-free exploit PoC generation from captured traffic.

Enables AI assistants to drive OWASP ZAP for authorized penetration testing and bug-bounty workflows, including authenticated scans and vulnerability triage through 67 curated safety-gated tools.

A stateful debugging and binary research system for LLM agents, integrating GDB + pwndbg with MCP for deterministic exploit workflows and multi-session support.

AI-powered security scanner for Python projects and GitHub repositories. Detects vulnerabilities, secrets, and provides AI risk assessment.

An MCP server that enables LLMs to query and reason over Active Directory attack graphs collected by BloodHound, providing attack paths, blast radius analysis, choke points, and defender remediation advice.

A Model Context Protocol server that enables AI assistants to search and retrieve information about security exploits and vulnerabilities from the Exploit Database, enhancing cybersecurity research capabilities.

Fully automated MCP server built to communicate with JADX-AI-MCP Plugin to analyze Android APKs using LLMs like Claude — uncover vulnerabilities, parse manifests, and reverse engineer effortlessly.

An MCP server for AI security analysis, enabling vulnerability scanning, sensitive information leak detection, and GitHub code leak monitoring via 48 tools.

An MCP server that measures how effectively hashing tool definitions detects unauthorized changes, evaluating 20 policies across field sets and canonicalization methods. It demonstrates that approval-dialog-based pins miss most attacks, with structural/semantic normalization being free but text folding trading detection for fewer false alarms.

Enables AI assistants to run WordPress site reconnaissance, malware/CVE security scans, SEO-spam/cloaking detection, and end-to-end natural-language goals through a stdio MCP interface, with the target site configured via environment variables.