"A Python library for visualizing neural networks" matching MCP servers:

Two-way Burp Suite MCP bridge enabling AI agents to capture traffic, analyze endpoints, queue scans, and send findings back to Burp.

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

GDB Enhanced Features MCP server for remote debugging and CTF exploitation with 41 specialized tools including ROP search, format-string detection, and memory patching.

Enables AI assistants to perform penetration testing and security assessments by exposing 60+ Kali Linux security tools including network scanning, web security testing, password cracking, exploitation frameworks, and OSINT capabilities through an AI-friendly interface.

Enables LLMs to perform automated penetration testing and Active Directory reconnaissance through Mythic, with tools for executing PowerShell, AD recon, domain user enumeration, and Kerberoasting.

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.

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.

Unified MCP server that gives AI agents security tools to audit MCP configs, redact secrets/PII, vet skills, check dependencies, and scan networks.

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.

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 Claude to scan a website's HTTP security headers and receive an A–F grade against OWASP best practices, including per-header pass/warn/fail results and copy-paste fixes for missing headers.

Enables interaction with Picus Security's Breach & Attack Simulation API, allowing natural language queries for simulations, threat library searches, and agent management through MCP-compatible clients.

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.

A Model Context Protocol (MCP) server for Gobuster that enables AI assistants to perform directory/file, DNS, virtual host, S3 bucket, and TFTP enumeration on a remote Kali Linux host via SSH.

Enables dynamic management and execution of proxy chains on a remote Linux host via SSH, allowing AI assistants to route network traffic through proxies for privacy and security testing.

A security gate MCP server that audits agent extensions (skills, MCP servers, tools) by scanning for risks, adversarial analysis, and sandbox execution, returning a trust verdict of allow, quarantine, or block.

A universal digital fingerprinting MCP server that combines 103 techniques across TCP, TLS, SSH, HTTP, DNS, and more into a single interface for AI agents, enabling full-spectrum fingerprinting on demand.

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

Enables AI assistants to perform web content discovery scans using feroxbuster on a remote system via SSH, with support for recursive scanning, filtering, and background execution.

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.