"Semgrep static analysis tool" matching MCP servers:

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

MCP server that detects and guards against tool poisoning and prompt injection attacks in tool descriptions and schemas. It provides risk scoring, pattern detection, safe rewriting, and audit reports with zero external API cost.

MCP security firewall (stdio): vet advertised tool definitions through static-scan → threat-feed → origin → pinning before they reach the model. Zero npm runtime deps. No secrets.

Enables scanning of Claude Code skills, plugins, or MCP servers for malware before installation via static analysis.

Enables AI agents to access VirusTotal intelligence through MCP, supporting file, URL, domain, and IP lookups, plus analysis, via remote HTTP or local stdio.

Enables AI assistants to search and analyze vulnerabilities and exploits from multiple intelligence sources, including NVD, CISA KEV, ExploitDB, Metasploit, and more, with tools for CVE research, exploit analysis, and report generation.

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.

Open behavioral litmus for MCP servers — grades A–F across tool-output injection, egress, sensitive-data, and adversarial-input, with reproducible, content-addressed evidence. Tools: run_litmus, verify_attestation.

Self-hosted MCP engine for private code reviews, providing deterministic static analysis and AST-level search over diffs, with findings passed to a review agent of your choice.

Provides a generic HTTP client tool allowing AI agents to make arbitrary HTTP requests from their environment, with support for environment-variable placeholders for secrets.

Static security scanner for AI-generated (vibe-coded) Supabase and Next.js apps. Runs as an MCP server so an LLM can scan, explain findings, and produce fixes while it writes code, all locally and offline.

Provides security audit primitives for MCP servers, agent tool schemas, and system prompts, along with pentest utilities like JWT inspection and HTTP diffing.

MCP server integrating Rizin reverse engineering, RzGhidra decompiler, and capa for binary analysis, enabling LLMs to open binaries, identify capabilities, extract function addresses, and decompile to C pseudocode.

Enables AI assistants to perform cybersecurity tasks including hash analysis, CVE lookup, HTTP header auditing, WHOIS/OSINT, payload decoding, password strength evaluation, and threat report generation.

Enables AI assistants to scan websites, public repositories, and OpenClaw/CLAW skills for security vulnerabilities, including local skill-package analysis before installation, cloud scans, and remediation guidance.

Converts Claude into a cybersecurity assistant by exposing 17 tools for network reconnaissance, cryptography, and security analysis, enabling users to perform tasks like SSL certificate checking, port scanning, and JWT analysis directly within conversations.

Automates Android app analysis using Frida via AI commands, connecting a rooted Android phone to a computer and running dynamic analysis scripts without manual command execution.

Connects LLMs to BloodHound Enterprise for natural language attack path analysis, Cypher queries, and exploration of Active Directory, Azure/Entra ID, and OpenGraph environments.

A production-grade security auditing MCP server that wraps semgrep (SAST) and gitleaks (secret detection) to enable one-click code security scanning via MCP stdio protocol.

Enables AI agents to orchestrate security research workflows by connecting to containerized security tools via MCP, allowing automated vulnerability analysis and pipeline execution.