"Latest Python Libraries and Their Purposes" matching MCP servers:

Exposes AI-augmented network reconnaissance and evasion capabilities as callable FastMCP tools, enabling natural language orchestration of host discovery, service fingerprinting, CVE mapping, and attack chain synthesis.

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.

Provides a generic HTTP client tool allowing AI agents to make arbitrary HTTP requests from their environment, with support for environment-variable placeholders for secrets.

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.

Enables searching and analyzing CVEs and vulnerabilities from multiple sources, optimized for PR review scenarios to help developers identify the latest security issues.

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.

Provides an MCP interface to a full Kali Linux environment running in Docker, enabling AI assistants to execute security tools like nmap, sqlmap, and metasploit. It allows users to start/stop the container, run shell commands, and transfer files for security testing and educational purposes.

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.

The Checkmarx Security MCP server bridges your AI assistant (Claude, Cursor, Copilot, etc.) with Checkmarx One's enterprise application security platform. It exposes security workflows as natural-language-accessible MCP tools, allowing developers to scan code, investigate findings, and receive context-aware fixes without leaving their development environment.

Enables an AI agent to perform authorized penetration testing through raw HTTP interaction, Python scripting, and shell commands, while providing an authorization wrapper to keep actions within an approved engagement context.

Audits MCP server configurations for security risks including capability inventory, SSRF, prompt injection, and drift detection. Works in read-only mode and can also be used as an MCP server to let AI agents audit their own attack surface.

A Python MCP server that decompiles Android APK/XAPK/JAR/AAR files and extracts HTTP APIs used by the app.

An MCP server that audits installed MCP servers, revealing their credentials, tool capabilities, and security risks. It enables users to assess and monitor the access granted to AI models.

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.

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

A security-focused MCP server that enables AI assistants to search PyPI packages, scan for vulnerabilities, audit dependencies, and ensure security across Python projects.

A local Python MCP server for safe, human-led bug bounty recon, providing lightweight helpers for scope checks, headers, robots.txt, sitemap.xml, JavaScript URL collection, endpoint extraction, URL deduplication, evidence notes, and manual test planning.

AI-orchestrated security testing via 6 Python tools (recon, port scan, subdomain hunting, frontend scanning, API fuzzing, and nemesis orchestrator) exposed as MCP tools for use by AI agents.

Enables AI agents to control and analyze RFID hardware through natural language: read, crack, emulate, and clone cards via MCP tools, with safety gates, offline dump analysis, and a host-side card library.