"Resources for Frontend Coding" matching MCP servers:

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.

MCP server for auditing infrastructure-as-code attack paths, finding multi-hop chains from public internet to sensitive resources.

Enables AI coding assistants to scan projects for security issues such as leaked API keys, missing Supabase RLS, open Firebase rules, unauthenticated routes, and hallucinated packages, then fix and verify the results.

Enables AI coding agents to search a security corpus, scan Terraform plan JSON for cited findings, and list sources via MCP tools grounded in CIS AWS Foundations and OWASP Top 10 CI/CD risks.

MCP server that enables AI coding tools to scan projects for security vulnerabilities, secret leaks, and compliance issues, generating Korean-language audit reports.

Scan a deployed site for an exposed Supabase service_role key and audit Row Level Security from your AI coding agent.

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.

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

Integrates Checkov, Semgrep, Bandit, and ASH to provide comprehensive code security analysis for AI coding assistants.

MCP server for TurboPentest — run AI-powered penetration tests and review findings from your coding assistant.

A local MCP server that scans repository dependencies for known vulnerabilities (CVEs) using OSV.dev, enriches findings with NVD and CISA KEV data, and supports triage, remediation, and accepted risk management directly from an AI coding assistant.

Free deterministic security scan of a public git repository (GitHub, GitLab, Codeberg, Bitbucket): vulnerable dependencies via OSV.dev, secret patterns, and config lint, returned as structured JSON. Tools: scan_repository(url), audit_pricing(). Runs locally over stdio (python3 web/mcp_stdio.py or the Dockerfile) and is also hosted at https://project-feldspar.com/mcp. MIT licence, stdlib-only. Buil

Security scanning for AI coding tools (Claude Code, Cursor, Windsurf) including secrets detection, MCP config vulnerabilities, agent instruction checks, threat modeling, prompt injection testing, pre-commit security checks, and dependency vulnerability scanning.

Enables AI coding agents to run sub-millisecond, fully offline CVE lookups and audit dependency manifests such as requirements.txt and package.json against known vulnerable version ranges. It returns CVSS severity details and calculates the minimal safe upgrade version needed to eliminate matching vulnerabilities, without rate limits or API keys.

Security scanner for vibe coders that checks npm packages for known vulnerabilities before installation, integrating with AI coding tools like Claude Code and Cursor.

An MCP security toolkit that integrates Burp-style HTTP proxying, AI-driven vulnerability hunting, source code auditing, and reporting into AI coding agents, enabling authorized security testing of web applications and source code.

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 developers and security teams to run evidence-first Android and iOS security audits, manage jobs and reports, query public vulnerability intelligence, evaluate policies, and plan runtime checks through stdio MCP tools and resources.

Exposes seven MCP tools that let an AI coding agent detect a project's stack, fetch the priority security checks for that platform, search 2,057 OWASP-derived check cards with file-and-commit provenance, and record evidence-backed pass/fail results in a report.

Provides local, dependency-free security scanning tools for LLM configurations, prompts, RAG sources, and more, enabling AI coding agents to detect prompt injections and other vulnerabilities without external network access.