"How to create the most intelligent agent" 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 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.

Security scanning, prompt injection detection, secret leak detection, and agent permission auditing for AI agent workflows.

Web3 Security & Honeypot Auditor for Base & EVM chains. Free bytecode selector analysis, DEX honeypot detection, DAO proposal scanner, and LLM audits.

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

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

Enables management of capture sessions, rules, certificates, and protocol communication through an MCP endpoint, controlling a sing-box core.

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.

A read-only MCP server that lets agents scan a project's AI agent setup — Claude Code, Codex, Cursor, MCP servers and instruction files — and surface security findings such as the lethal trifecta, broad permissions, exposed secrets and unpinned packages.

Enables coding agents to scan a public URL in passive or authorized mode and receive only bounded, sanitized structured findings (severity, confidence, standard, evidence, remediation) with quarantined evidence instead of raw page dumps. A second tool lets agents inspect the scanner's safety boundaries and coverage without making any network request.

Security scanner for MCP servers. Detects prompt injection, command injection, auth bypass, and excessive permissions across tools, resources, and prompts.

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.

Enables MCP-compatible agent hosts to delegate governed, read-only security audits and reviews of code, applications, agents, prompts, MCP configurations, and cloud environments through evidence-first findings and stable schemas.

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

Integrates ProjectDiscovery security tools to perform automated reconnaissance, subdomain discovery, and vulnerability scanning. It enables comprehensive bug hunting workflows by chaining tools like subfinder, naabu, and nuclei into a unified pipeline.

A security scanner for AI coding agents and autonomous assistants that scans code for vulnerabilities, detects hallucinated packages, blocks prompt injection, and provides LLM-powered semantic code review via MCP or CLI.

Enables real-time injection fuzzing and canary-based exfiltration detection over untrusted prompts, RAG context, and agent actions, with entropy analysis, outbound channel interception, least-privilege sandboxing, and cryptographic audit proofs.

Enables MCP clients to carry out a compliant, non-destructive, auditable authorized security-testing workflow — project intake, scope reading, asset discovery, non-destructive verification, evidence collection, and report-draft generation with manual submission tracking — where every outbound action is gated by scope checks, one-time human confirmation tokens, rate limits, and append-only audit logging.

Enables a language model to inspect proxy history, run scoped scans and intruder jobs, and drive a proxied browser through Burp Suite for authorized security testing on test and staging environments. Scope, environment, mode, rate limits, refusals and secret redaction are enforced in gateway code with a tamper-evident audit log.

Enables users to scan AI agent skills and configuration files for hidden Unicode instructions, prompt injection, download-and-execute payloads, exfiltration patterns, and overly broad permissions before installation. It provides static audit tools for skill files, agent configs, and revealing hidden text without executing or fetching the input.

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.

Provides safe network reconnaissance through DNS resolution, TLS inspection, HTTP security header grading, and bounded port scanning over the stateless MCP protocol.

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.

A model-neutral cyber capability brain for AI agents and human researchers, providing MCP tools for knowledge ingestion, composition, campaign planning, fleet management, evidence binding, and discovery replay.

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

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.

MCP server for AI-powered code security, quality, and performance review. Enables auditing code directly from VS Code via right-click or MCP tools.

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

Offers a control surface for AI agent security with four independent checks: source-code scanning, tenant isolation, LLM content verification, and deploy gating. Currently in pre-release, with no functional scanning engines yet.

Penthera checks your repo, dependencies, AI agent config (hooks, MCP servers, skills) and your own live site, on your machine. Rules decide every finding; a model never does. Your agent gets a short brief: what to act on, what to check first, what's likely noise and what wasn't checked. Free and open source (MIT), offline by default, no account, no telemetry.

Performs static security analysis of Solana programs and generates x402 payment invoices for automated agent-to-agent audit workflows.

A Codex-style MCP server providing 126 tools to operate a Kali Linux machine from ChatGPT or any compatible MCP client, including shell execution, filesystem operations, Git, Docker, browser automation, and security tool wrappers.

Enables agents to generate tamper-evident SHA-256 Merkle audit trails, produce logarithmic inclusion proofs, and verify integrity through a STDIO MCP interface.

Provides a set of MCP tools to clone and analyze arbitrary MCP server repositories, run static and dynamic security probes in isolated Docker containers, and produce vulnerability verdicts with a human-in-the-loop approval step before filing public reports.

This MCP server enables real-time injection fuzzing, exfiltration canary detection, least-privilege tool sandboxing, and cryptographic Merkle audit proofs for agent prompts, RAG context, and actions. It provides tamper-evident SHA-256 tree generation, logarithmic inclusion proofs, and verifiable integrity checks through MCP.

Enables agents to inspect and automate Caido web-audit data through MCP tools, including request history, WebSockets, sitemap entries, and environments, with grouped permissions, bounded confirmations, and credential redaction for controlled operation.

Enables MCP-compatible agents to submit source code for automated SAST/SCA security audits paid via x402 USDC micropayments on Base, returning structured vulnerability findings, CWE IDs, and optional remediated code patches.

Enables LLM clients to conduct authorized penetration testing and CTF challenges through a multi-mode agent with evidence-chain anti-hallucination, skill evolution, and MCP tool orchestration.

Enables AI agents and MCP servers to operate under autonomous security enforcement, including pre-deployment scanning, per-call authorization, runtime monitoring, incident containment, and comprehensive auditing.

Enables users to compute credential bit entropy and GPU brute-force cracking timelines, audit cross-account password reuse exposure, and perform k-anonymity hash-prefix privacy checks without leaking credentials.