"Tool or method to fetch and explain the latest version of code from a repository" 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.

Enables MCP-compatible agents to audit an entire repository through one question, detecting stacks and running parallel checks for dead code, dependencies, security, CVEs, complexity, and lint across Laravel/PHP, Python, TypeScript/React, and Flutter/Dart. It returns normalized, severity-sorted findings with false positives flagged and secret values kept out of the output.

Enables AI assistants to natively execute and manage 600+ Kali Linux security, penetration testing, and forensic tools, including search, help documentation, structured scanners, and workspace management.

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.

Enables automated security code auditing using LLM and MCP, including AST parsing, taint analysis, dataflow tracing, and automated PoC generation for multi-language codebases.

Multi-language SAST and AI-powered fuzzing MCP server for Claude Code integration, enabling static and dynamic security analysis of code.

MCP server that detects and guards against tool poisoning and prompt injection attacks in tool descriptions and schemas. It provides risk scoring, pattern detection, safe rewriting, and audit reports with zero external API cost.

Enables AI coding assistants to run static analysis on GitHub repositories, raw code snippets, or local directories to detect cloud cost leaks in Terraform/AWS configs, PostgreSQL migration table-lock hazards, and OWASP/Next.js API security gaps. Each finding returns structured severity, line-level detail, and drop-in fixes.

Enables security testing of MCP guardrails and SAST scanners by exposing intentionally vulnerable code patterns that are inert by default and make no network calls.

Scans GitHub repositories for security vulnerabilities by cloning, performing static analysis, secret detection, build verification, and AI-powered OWASP-aligned code review, producing a scored SECURITY.md report.

MCP server that guides LLM security reviews step-by-step, tracking progress and ensuring all assigned source code is read before completing each plan step.

Enables coding agents and CI/CD pipelines to audit untrusted code by detecting Python sandbox escapes, SQL injection taint, ReDoS regex vulnerabilities, and CORS misconfigurations, while generating Seccomp BPF filters for safer execution.

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.

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

An AI-native code security audit MCP server that supports multi-language AST analysis, call graph analysis, vulnerability detection, and AI deep audit.

Enables AI-powered automated testing, security scanning, code review, and maintenance tasks directly within Claude Code or desktop.

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 authenticated remote MCP clients to manage a Kali Linux environment, run modular tools in sandboxed or optional host contexts, configure networking, and monitor jobs through a live WebUI.

Enables AI coding agents to audit websites for PHP runtime vulnerabilities, compile a live Zero-PHP Next.js App Router replacement preview from a WordPress/PHP site, and retrieve remediation guidance.

Cyber Host Artificial Intelligence (C.H.A.I) An autonomous penetration testing MCP (Model Context Protocol) server with an integrated AI decision engine, multi-provider LLM support, and an extensible plugin architecture.

Enables users to run synthetic support-agent evaluations, preserve and inspect traces, score results deterministically, inject failures, and enforce release review gates through MCP tools, resources, and prompts.

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.

Code review as an MCP server — structured code quality reviews with OWASP security scanning.

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

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.

Enables users to audit EVM, Solana, and Move smart contracts and assess Web3 security risks through tools for honeypot detection, SPL token risk, MEV sandwich exposure, address poisoning, HTTP 402 invoice fraud, UTXO consolidation planning, and cross-chain bridge quotes.

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

Enables agents and operators to audit MCP tool permissions for least privilege, score blast radius, detect privilege-escalation chains, verify capability matrices, and produce cryptographic audit proofs with injection fuzzing and exfiltration canaries.

Enables scanning of AI agent code for security vulnerabilities such as prompt injection, tool abuse, and data exfiltration, directly from MCP-compatible clients like Claude Code.

Exposes an assess_repo tool that scans a repository, local folder, or npm/PyPI package and returns supply-chain risk findings with file, line, and code evidence — install-time scripts, dangerous patterns, secrets, AI-agent manipulation, impersonation and published-artifact mismatches — while never executing the target's code. Findings carry severities from info to critical so results can gate installs and CI jobs.