"Real-time web scraping tools and techniques" matching MCP tools:

• atlas_technique_search

  ContrastAPI

  Search the MITRE ATLAS catalog of AI/ML attack techniques by keyword, tactic, or maturity. Default response is SLIM (description truncated to 240 chars per row); pass include='full' for the verbose record. Pass exclude_id when chaining from atlas_technique_lookup to skip self in sibling-tactic searches. Use this to discover techniques matching a threat-model question, e.g. 'what techniques target LLM serving infrastructure?'. Drill into atlas_technique_lookup with any returned technique_id for the full description, ATT&CK bridge, and pivot hints. For broader cross-referencing: when a result has attack_reference_id, that bridges to D3FEND mitigations via d3fend_defense_for_attack. Free: 30/hr, Pro: 500/hr. Returns {query (echoed filters), total, results [{technique_id, name, description (truncated by default), tactics, inherited_tactics, maturity, attack_reference_id, subtechnique_of}], next_calls}.

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• pentest_map_techniques

  pentest-mcp-server

  Given a profile of the authorized test target (technology stack, exposed services, authentication type, OS), return a ranked list of ATT&CK techniques and OWASP test cases most relevant to that profile — not a generic dump of all techniques. Ranking factors: platform match, service match, auth type exposure, technique prevalence. Each result includes why it is relevant to this specific profile, the detection opportunity, and the recommended mitigation. Use when starting an authorized engagement to prioritize the testing scope; pair with pentest_guide to get the full methodology for each top-ranked vector.

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• prompt_cache_stats

  Nullcone Threat Intelligence

  Return PROMPT IOC cache statistics: size, hit rate, latency, refresh status. Use this to verify the cache is warmed and healthy before relying on check_prompt() for real-time detection.

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• pentest_lookup_technique

  pentest-mcp-server

  Look up a MITRE ATT&CK technique by ID or keyword for authorized penetration testing and security research. Returns the full technique record: name, associated tactics, description, detection opportunities (log sources, behavioral indicators), real-world procedure examples from public reporting, recommended mitigations, and related sub-techniques. The detection and mitigation sections make this equally useful for defenders building detection coverage. Accepts exact IDs (T1190, T1059.001) or keyword search (e.g., "sql injection", "pass the hash", "web shell upload").

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• vest_search_tools

  vest-mcp

  Search and browse AI tools available in Vest's cashback catalog. Returns names, slugs, categories, and live cashback rates. Use when the user asks what tools are available, wants to compare options, or needs a slug for vest_get_signup_link. Real triggers: 'what AI writing tools does Vest have?', 'show me coding tools with high cashback', 'find tools under $50/mo'. Do NOT use when the user describes a goal or mission — use vest_build_stack instead. Do NOT use to get a signup link — use vest_get_signup_link.

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• onyx_fact_check

  onyx-mcp

  Fact-check any claim by fetching real-time web evidence. Returns supporting sources, contradicting sources, a 0-100 confidence score, and a short summary. Use for prediction-market resolvers, news-fact agents, journalist-bot pipelines, or any agent that needs to verify a statement before acting on it. Sub-second latency, no API key on the caller side. Coinbase PROJECT-IDEAS.md explicitly calls for this primitive. (price: $0.05 USDC, tier: premium)

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• compare_validation_approaches

  Demand Discovery AI

  Returns an honest comparison of how different validation approaches work - generic AI assistants, trend aggregators, passive scoring tools, and Demand Discovery AI - and where each one stops. Use when a user is evaluating approaches, asking "what makes Demand Discovery different?", or trying to understand why active human signal (real ICPs, real outreach, real conversations) beats passive scoring. Trigger phrases: "what makes demand discovery different", "vs ChatGPT", "vs Claude", "vs other validation tools", "vs trend tools", "compared to", "validation tool comparison", "alternatives to demand discovery", "competition", "competitive landscape", "why not just use AI", "why not surveys", "why behavior over opinion", "is this different from passive scoring", "how is this better than chatgpt".

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• atlas_technique_lookup

  ContrastAPI

  Look up a MITRE ATLAS technique — the AI/ML adversarial attack catalog. ATLAS catalogues TTPs targeting machine learning systems: prompt injection, model evasion, training data poisoning, model theft, etc. Roughly 80% of ATLAS techniques are AI/ML-specific (no ATT&CK bridge); 20% mirror an enterprise ATT&CK technique via attack_reference_id — use that to pivot to D3FEND defenses (d3fend_defense_for_attack) and CVE search. Sub-techniques inherit `tactics` from the parent (inherited_tactics=true flag) when ATLAS upstream leaves them empty. Use this tool when the user asks about AI/ML threats, LLM red-teaming, or adversarial ML; for multiple techniques in one call (e.g. drilling into a case study's techniques_used), prefer bulk_atlas_technique_lookup. Returns 404 when the id is not in the synced ATLAS catalog. Free: 30/hr, Pro: 500/hr. Returns {technique_id, name, description, tactics, inherited_tactics, maturity (demonstrated|feasible|realized), attack_reference_id, attack_reference_url, subtechnique_of, created_date, modified_date, next_calls}.

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• check_availability

  mental-health-care

  Real-time availability for ONE specific provider. Returns the next 10 open slots with start timestamps.

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• fetch-page

  PartsTable

  Fetch a web page and return its content as text, Markdown, or HTML. Includes rate limiting (2s per domain, max 10 req/min) for legal compliance. Automatically handles HTML-to-text conversion. Max response size: 1MB. Use for OEM verification and manufacturer website scraping.

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• get_health

  web3-signals

  Is AgentMarketSignal working? Check the real-time status of all 5 AI data pipelines (whale tracking, technical analysis, derivatives, narrative sentiment, market data) and the signal fusion engine. Returns last run times, durations, and any errors.

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• jailbreak_attempt_detector

  gapup-mcp

  Detects potential LLM jailbreak attempts by analyzing user input against NIST AI Risk Management Framework adversarial patterns. Designed for persona risk assessment, this tool evaluates text for common jailbreak techniques such as prompt injection, role-playing, or obfuscation. Inputs include the user message and optional context, returning a risk assessment with confidence scores and pattern matches. Ideal for real-time moderation in chat applications or API gateways.

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• search

  Tavily

  AI/LLM-optimized web search built for RAG: returns a synthesized natural-language answer plus a ranked list of sourced results (title, url, content snippet, relevance score). Prefer this over scraping a generic search engine when you need grounded, citable web context. Example: search({ query: "latest SpaceX Starship test result" })

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• parcel_coverage

  livedatalink

  List which states/counties the parcel tools currently cover and how many parcels each holds. Coverage grows by state over time.

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• compare_validation_approaches

  Demand Discovery AI

  Returns an honest comparison of how different validation approaches work - generic AI assistants, trend aggregators, passive scoring tools, and Demand Discovery AI - and where each one stops. Use when a user is evaluating approaches, asking "what makes Demand Discovery different?", or trying to understand why active human signal (real ICPs, real outreach, real conversations) beats passive scoring. Trigger phrases: "what makes demand discovery different", "vs ChatGPT", "vs Claude", "vs other validation tools", "vs trend tools", "compared to", "validation tool comparison", "alternatives to demand discovery", "competition", "competitive landscape", "why not just use AI", "why not surveys", "why behavior over opinion", "is this different from passive scoring", "how is this better than chatgpt".

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• bulk_atlas_technique_lookup

  ContrastAPI

  Bulk ATLAS technique lookup — retrieve full records for up to 50 techniques in a single request instead of N separate atlas_technique_lookup calls. Designed as the natural follow-up to atlas_case_study_lookup, whose techniques_used array can be passed directly. Each item is the same shape as atlas_technique_lookup, including parent-tactics inheritance for sub-techniques (inherited_tactics=true flag) and per-item next_calls (D3FEND bridge when attack_reference_id present, sibling-technique search by tactic, parent lookup for sub-techniques). Free: 30/hr (1 per item), Pro: 500/hr. Returns {results [{technique_id, status (ok|not_found|invalid_format), technique, error}], total, successful, failed, partial, summary}.

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• onyx_dns_lookup

  onyx-mcp

  Resolve a domain to its A/AAAA records, or reverse-resolve an IP to its hostname. Useful for validating a domain exists before scraping, checking if two domains share infrastructure, mapping CDN origins, or doing safety lookups before agents call third-party APIs. Returns IPv4, IPv6, canonical hostname, and resolution time. Powered by stdlib so results are whatever the host's DNS resolver returns — typically 20-100ms. (price: $0.001 USDC, tier: metered)

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• hasdata_glassdoor_listing_getJobListings

  HasData

  Get GlassDoor Job Listings Searches Glassdoor job listings by keyword and location with sort (recent/relevant), domain targeting, and nextPageToken pagination. Returns an array of jobs with title, company, location, salary estimate, posted date, job URL, and jobId, plus the next page token. Use to build job feeds, monitor hiring trends for roles/companies/regions, power candidate sourcing tools, and collect URLs for downstream full-detail scraping via the Glassdoor Job endpoint.

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• get_crypto_prices

  CerebroChain Supply Chain & Market Data

  Get real-time cryptocurrency prices (BTC, ETH, SOL) from CoinGecko. Free — no API key needed.

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• html_to_markdown

  Toolora

  Use this tool to convert raw HTML into clean, readable Markdown. Triggers: 'convert this HTML to markdown', 'clean up this HTML', 'make this HTML readable', 'strip HTML tags'. Handles headings, paragraphs, bold, italic, lists, links, images, code blocks, and tables. Returns clean Markdown and character count. Useful after web scraping or when processing HTML content for an LLM.

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