"AWS Cost and Usage Analysis with Cost Optimization Recommendations" matching MCP servers:

Federates multiple local debugging MCP backends behind a single authenticated MCP endpoint, enabling unified access to Cheat Engine, x64dbg, and x32dbg tools.

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

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 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.

MCP server for AgentMinds collective intelligence platform, enabling AI agents to scan websites for security/SEO/performance issues, pull personalized recommendations, and share findings across the network.

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.

Exports vulnerability and asset data from Rapid7 Command Platform via the Bulk Export API into a local DuckDB database, enabling AI assistants to run natural language queries and SQL analysis with sandboxed security.

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.

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.

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.

Enables bug bounty hunters to browse programs, inspect scope details, track scope changes over time, and receive personalized, recency-boosted program recommendations based on their skill profile.

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.

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

Security scanning for MCP servers from the inside out. Provides runtime inspection, AST-based static analysis, config audit, dependency analysis, and OWASP MCP Top 10 compliance in a single MCP server.