"MCP servers for full-stack development, DevOps, Supabase, QA, and AI agent orchestration" 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 auditing a Supabase project's security beyond the dashboard's Security Advisor, checking anonymous access, RLS policies, and cross-tenant data leaks via read-only probes and a two-account test.

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.

Enables passive security scanning of HAR files from QA test automation to detect missing security headers, insecure cookies, CORS misconfigurations, and leaked secrets, without making any live requests.

MCP server for AI-driven VAPT orchestration, enabling agents to plan and execute authorized security scans through a control plane that enforces scope, sanitization, budget, rate limits, human approval, and audit logging.

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.

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.

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

An authorization-first MCP-governed control plane for executing security-tool workflows in explicitly approved, sandboxed environments with auditable campaigns and AI collaboration boundaries.

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

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.

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.

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

Enables AI agents to plan and run authorized offensive security assessments across 150+ integrated tools, with full activity logging of every scan.

Autonomous pentests from one command: real security tools, working PoCs, and audit-ready reports, all driven via MCP.

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.

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

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 natural-language-driven security testing by orchestrating multiple pen-testing tools through MCP, with automated scan execution and AI-assisted vulnerability summarization.