"F-Droid" matching MCP servers:

Provides email validation and domain configuration auditing tools for AI assistants, enabling single address checks, bulk list cleaning, SPF verification, and full mail setup grading (A-F) with actionable fixes.

Enables AI agents to scan payment endpoints for safety, returning a letter grade (A–F) and verdict before authorizing payments.

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.

A neutral, public danger grade for MCP servers that AI agents rely on, providing A-F grades and transparency signals to vet servers before connecting.

Mandatory human approval gate for autonomous AI agents. Before any critical, irreversible, or financially significant action executes — file deletion, production deployment, financial transaction — the agent calls oracle_validate. A human receives a real-time Telegram notification with full context and taps Approve or Reject. The agent waits for the decision before proceeding.

Enables Claude to run safe, read-only diagnostics against servers and websites — certificate chains and expiry, HTTP status/redirects/security headers, DNS records, email authentication (SPF, DKIM, DMARC, MTA-STS, TLS-RPT) and sitemaps. Every check returns severity-tagged findings with concrete fixes, plus a 0-100 score and A-F grade, without any ability to modify the target.

Domain security reconnaissance for AI agents — 13 tools (DNS+DNSSEC, SSL/TLS, HTTP security headers, SPF/DKIM/DMARC email auth, port scan, ASN, RDAP/WHOIS) plus a one-shot security_scan returning a 0–100 Health Score (A–F). Free, no API key.

Enables live website health checks including TLS, HTTPS, and security headers, returning an A-F grade with specific fixes.

Enables Claude to scan a website's HTTP security headers and receive an A–F grade against OWASP best practices, including per-header pass/warn/fail results and copy-paste fixes for missing headers.

Supply chain risk scoring for npm, PyPI, and GitHub repos

Gives AI assistants access to F6 XDR alerts, incidents, emails, files, hosts, and audit logs via query-language search, with tools for counting records, inspecting available fields and filters, and marking events.

Enables AI coding agents to plan, policy-check, and cost-estimate Terraform changes while requiring human approval through Slack or CLI before any terraform apply can execute.

Enables AI agents and developers to audit any URL or domain for seven critical OWASP HTTP security headers, returning an A+ to F grade plus actionable Nginx, Apache, Caddy, and Cloudflare remediation snippets. It also probes /.well-known/security.txt and /security.txt to surface responsible vulnerability disclosure contacts, bug bounty scopes, and PGP keys.

Checks a code repository without running it: Safe, Works and Complete scores with an A-F grade, catching leaked keys, dangerous calls, invented or lookalike packages, broken imports and missing project files. Standard-library Python; MCP tools scan, orphans and explain.

Read-only Cloudflare MCP server for SOC investigation, exposing Cloudflare services like WAF, bot management, analytics, and Zero Trust for querying and discovery.

A local stdio MCP server that enables coding agents to discover credential handles and create scoped action requests with local approval and sanitized output.

Autonomous M2M compliance and trust APIs for AI agents (KYB, OFAC, VAT, Sanctions checking).

Enables triage, installation validation, and controlled automation of X-Ways Forensics and related tools through structured MCP tools for agents.

Enables LLM clients to safely perform file operations such as create, read, edit, delete, move, copy, and more, with every path checked against an explicit permission database managed through a desktop GUI.

缔零法则MCP是基于LLM和RAG技术搭建的实现完全替代人力的全自动化风险识别的内容安全审查平台，致力于通过代理AI技术减少人力成本，高效高精度为用户提供分钟级接入的内容风控解决方案，破解安全威胁，提供从风险感知到主动拦截策略执行的全链路闭环与一体化解决方案。This MCP tool is an AI-powered content security review platform built on LLM and RAG technologies, designed to achieve fully automated risk identification that completel