"Security testing, penetration testing, and code auditing services" matching MCP servers:

Provides access to over 40 industry-standard penetration testing tools, including Nmap, SQLMap, and Metasploit, within an isolated Kali Linux Docker container. It enables security professionals to perform comprehensive network reconnaissance, web application testing, and vulnerability research through natural language commands.

Exposes browser-testing capabilities—including navigation, clicking, typing, form submission, verification, and screenshots—so clients can discover the supported Playwright actions. It also builds structured testing requirements from a supplied website and task description, ready for plan generation and execution.

Orchestrates end-to-end testing of AI-powered incident remediation workflows through declarative YAML scenarios, fault injection, AI response evaluation, and automated command execution with comprehensive reporting.

Integrates 193 Kali Linux security tools with AI for intelligent penetration testing, CTF solving, and vulnerability assessment through automated workflows and expert knowledge base.

Pay-per-use AI security and research tools for autonomous agents on Base, enabling honeypot detection, risk assessment, wallet analysis, and yield optimization via the x402 protocol.

Provides self-healing UI/API test automation via Plan-Generate-Run-Heal cycle, exposing MCP tools for test platforms to trigger batches and retrieve reports.

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.

Protects AI agents from threats like prompt injection, jailbreaks, and SQL injection through a multi-layer scanning pipeline. It also enables PII redaction and rehydration to ensure data privacy during LLM interactions.

Enables multi-agent council workflows for coding assistants, providing parallel independent reviews, plans, brainstorms, validation, and research with strict read-only boundaries.

Zero-trust safety & settlement rail for autonomous AI agents. Sub-10ms deterministic guardrails, secret leak defense, bounded wallet controls, and on-chain Proof-of-Safety attestations via x402.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Provides access to a library of 18 specialized skills, project templates, and prompt patterns for Claude Code. It enables automated workflows for feature development, security audits, and system maintenance through multi-agent collaboration.

A security filter that blocks dangerous code patterns by comparing normalized structural syntax trees against a blacklist of known threats using vector embeddings. It acts as a gatekeeper to prevent malicious code execution by identifying dangerous structures regardless of specific identifiers or literals.

Turns AI assistants into full-stack software engineers with 36 tools for cognitive reasoning, code validation, project scaffolding, and AI/IDE configuration generation across 130+ programming languages, databases, and frameworks.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Provides coding agents with typed classification, yes/no checks, scoring, ranking, and question-answering tools that return calibrated probabilities for fast, reliable decisions.

Provides automated security incident remediation tools for AWS, enabling real-time threat response by quarantining malicious S3 objects, restricting IAM access, and updating security groups.

Unifies 7,283+ detection rules from Sigma, Splunk ESCU, Elastic, and KQL into a single queryable interface via MCP, with a web dashboard and autonomous agent pipeline for detection engineering.

An AI-powered security agent that utilizes MCP tools and Groq LLMs to analyze Azure infrastructure, audit security groups, and identify storage misconfigurations. It enables users to perform natural language security assessments and ensure compliance with CIS Azure best practices.

Enables Codex to delegate long-running work to Claude Code via blocking MCP calls, with tools for model discovery, run, and resume without polling.