"Web login and content scraping tutorial" matching MCP servers:

An MCP server that lets an AI agent probe a live URL and confirm whether sensitive files (e.g., .git, .env, source maps) are genuinely served by fetching and validating the content, avoiding false positives.

MCP server that exposes 31 OSINT checks from Lissy93/web-check as tools for website analysis, including SSL, DNS, headers, WHOIS, and security presets. Enables natural-language-driven web recon and health checks.

Enables AI agents to audit URLs for security headers, generate CSP Level 3 policies, compute SRI hashes, evaluate WCAG 2.2 contrast, and remediate headers.

Connects AI coding assistants to Snyk API & Web for onboarding scan targets, configuring authentication, running DAST scans, and triaging findings through natural language.

Enables proof-backed code audit via MCP tools for AST-based code maps, symbol lookup, callers, audit commands, and persistent verdict memory.

Enables users to run synthetic support-agent evaluations, preserve and inspect traces, score results deterministically, inject failures, and enforce release review gates through MCP tools, resources, and prompts.

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 agents to inspect web pages for Cloudflare Turnstile challenges without an API key, and clear Turnstile or WAF challenges using a SolveGate API key.

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

Offers a control surface for AI agent security with four independent checks: source-code scanning, tenant isolation, LLM content verification, and deploy gating. Currently in pre-release, with no functional scanning engines yet.

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.

Enables AI agents to drive live Hack The Box labs through the real HTB Labs API — spawning, resetting and extending machines, submitting user and root flags with difficulty ratings, browsing challenges, and switching or downloading VPN configurations for the authenticated account. Every call hits the live API rather than cached content, with destructive actions annotated so hosts can gate them behind consent.

Runs WCAG accessibility, SEO, performance, and security audits on URLs or raw HTML via SiteLint Auditor. Enables LLM agents to audit web pages and check WCAG criteria through MCP tools.

Enables policy-first defensive security operations for MCP, providing repository and web-security analysis with controlled authorization, scoped execution, and auditability.

Chrome browser JS reverse engineering MCP tool for CTF/Web security, enabling dynamic analysis and restoration of login encryption logic.

Enables AI assistants to perform web content discovery scans using feroxbuster on a remote system via SSH, with support for recursive scanning, filtering, and background execution.

An MCP server for identifying SQL injection vulnerabilities in web applications using various techniques like error-based, time-based, and union-based scanning. It supports bulk URL processing, WAF bypass strategies, and authenticated testing across multiple database systems.

Enables AI assistants to execute security testing tools on a Kali Linux machine over SSH, including reconnaissance, web app scanning, and static/dynamic analysis.

A comprehensive MCP server for web security reconnaissance, providing tools for passive and active information gathering, DNS analysis, network scanning, and web application analysis.

Enables AI applications to invoke 58 popular Kali Linux security tools for network scanning, web exploitation, password attacks, reconnaissance, Metasploit, evasion, forensics, post-exploitation, and miscellaneous tasks through the Model Context Protocol.