"Learning to Create an Expert Python Program to Exit 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.

Wraps Kali Linux penetration testing tools for authorized security assessments, driven by a local LLM via LM Studio.

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.

Enables to search and analyze internet-connected devices using the Shodan API, with tools for host search, DNS, scanning, exploits, alerts, and more.

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.

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.

GhostHunt is an MCP server that scans your development machine for API keys, tokens, and credentials hiding in places you forgot to check.

Enables bug bounty hunters to browse programs, inspect scope details, track scope changes over time, and receive personalized, recency-boosted program recommendations based on their skill profile.

A scope-aware bug-bounty & reconnaissance MCP server that works out of the box on the Python standard library and augments itself with your favourite CLI tools when they're present.

Gives AI agents a browser that bypasses bot detection, a MITM proxy for traffic interception, and a Python sandbox to autonomously write and execute security exploits.

Enables AI assistants to run Kali Linux security tools in an isolated Docker container for tasks like network scanning, port checking, and service enumeration.

An MCP server that exposes Prof. Null, an uncensored cybersecurity professor, as a set of specialized tools for learning hacking, CTFs, and security concepts through Q\&A, roadmaps, cheatsheets, labs, and more.

Exposes a pentest toolbox (sqlmap, nuclei, ffuf, etc.) via Docker to an LLM orchestrator for authorized security audits, with strict whitelisting and timeout controls.

An intentionally vulnerable MCP server for security training, enabling users to practice attacking and defending AI agents through realistic scenarios.

Provides 28 MCP tools across 16 analysis engines for comprehensive Python code quality assessment, including complexity scoring, security scanning, dead code detection, dependency auditing, and test quality analysis.

Enables out-of-band interaction testing by integrating ProjectDiscovery's interactsh service as an MCP server. Allows AI agents to create callback domains, send probes, and capture DNS/HTTP interactions for security testing and verification workflows.

An MCP server that provides passive and low-impact active reconnaissance tools for authorized bug bounty and security assessments, enabling LLMs to perform structured recon and generate reports.

An MCP server that provides AI assistants with access to CrackMapExec/NetExec network penetration testing capabilities via SSH to a Kali Linux host, supporting multiple protocols for enumeration, credential dumping, and command execution.

A local, read-only MCP server that connects your HackerOne researcher account to Claude Desktop and Claude Code, helping you find targets, analyze program scopes, review reports and earnings, and draft bug reports.

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.