"Chat with RAG (Retrieval-Augmented Generation)" matching MCP servers:

Enables AI agents to perform offline cybersecurity research and penetration testing by querying a local knowledge base of curated security data, with tools for searching, answering, and status checking.

Exposes AI-augmented network reconnaissance and evasion capabilities as callable FastMCP tools, enabling natural language orchestration of host discovery, service fingerprinting, CVE mapping, and attack chain synthesis.

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.

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.

Multi-engine container and system vulnerability scanning for AI agents. Wraps Trivy and Grype with cross-engine validation, SBOM generation, and IaC misconfiguration scanning.

Unified MCP server integrating NIST and OWASP security frameworks with live vulnerability data, enabling security searches, compliance mapping, threat modeling, and checklist generation.

A real security scanning MCP server for medical information systems, supporting port scanning, vulnerability detection, medical system identification, and compliance report generation.

Enables agents to store, search, and manage a personal penetration testing knowledge base via MCP, using BM25-ranked retrieval with Chinese tokenization, plus draft approval, deduplication, and sensitive-data redaction workflows.

MCP server that enables LLMs to operate Acunetix/Invicti web vulnerability scanners through 15 tools, covering authentication, target management, scanning, vulnerability retrieval, and reporting via GraphQL and REST APIs.

Enables guided security evaluation of a virtual lab machine, including network scanning, HTTP/TLS analysis, OWASP Top 10 assessment, and Markdown report generation, without performing exploitation.

A security-focused server that integrates with Cursor IDE to provide real-time vulnerability detection, exploit generation, and security insights during software development.

Read-only MCP server for precise lookup, search, and versioned retrieval of OWASP testing guides (WSTG, MASTG, ISTG, AITG) with full provenance on every result.

Enterprise-grade zero-dependency security shield and runtime governance engine for MCP servers, providing OWASP MCP Top 10 audits, cryptographic tool call signing, AIBOM generation, and inline parameter firewall protection.

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.

A Model Context Protocol server for the Sliver C2 framework that exposes operator tools like listeners, implant generation, sessions, command execution, and file operations for LLM-driven adversary emulation.

Enables cybersecurity training, purple-team collaboration, and executive readiness through tools for scenario generation, attack simulation, telemetry analysis, incident investigation, forensics, and reporting with an immutable audit trail.

Enables LLMs to perform Active Directory penetration testing using tools like NetExec, Bloodhound, Nmap, Certipy, and John the Ripper. Automates vulnerability discovery, attack path analysis, and documentation generation for security assessments.

Enables AI agents to orchestrate 25+ security tools for penetration testing through natural language, automating scans, vulnerability detection, and report generation.

A Model Context Protocol (MCP) server for integrating with StackHawk's security scanning platform. Helps developers set up StackHawk, run security scans, and triage findings to fix vulnerabilities — all from within an LLM-powered IDE or chat.

Provides on-machine security scanning for Copilot-generated code, including SAST, secrets, dependency, container, and configuration checks, plus AI-specific risk detection, with findings and fixes available via MCP tools.