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281,193 tools. Last updated 2026-07-10 06:07

"Techniques for Scraping Publicly Accessible Documents" matching MCP tools:

  • Download a PDF from a URL and extract all text content, page by page. Use this to read the full text of a specific document — for example, an annual report PDF linked from a search_filings result. Best combined with search_filings: use search_filings to locate the document, then parse_pdf_to_text for the full text. Do not use for PDFs that are already well-represented in the database — search_filings is faster and returns pre-ranked, relevant excerpts. Not suitable for scanned (image-only) PDFs without embedded text; those pages will be returned as "(no extractable text)". Args: pdf_url: Direct HTTPS URL to the PDF file, e.g. https://example.com/report.pdf. Must be publicly accessible; authentication-protected URLs will fail. Returns: All text from the PDF with "--- Page N ---" separators between pages. Returns an error string if the download fails, the URL does not point to a valid PDF, or the document exceeds the 60-second download timeout.
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  • Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64, base64-encoded JPEG/PNG, with or without data URI prefix. image_url, publicly accessible image URL (max 5 MB). image_chunks, array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap, resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...
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  • 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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  • 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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  • Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.
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  • Return canonical synthesis / patching techniques with role-keyed module realizations drawn from the corpus. Use this when the user asks "how do I do X?" with X being a recognisable technique (low-pass-gate plucks, pinged-filter percussion, parallel multiband processing, complex-oscillator FM, karplus-strong pluck, clocked-delay feedback, modal-resonator excitation, wavefolder harmonics, envelope-follower ducking, Maths-style function-generator omnibus). It's also the right tool when the user has a module and asks "what's this good for?" — pass filter.module_id to retrieve every technique that references the module via its role_realizations. Each technique declares role_definitions (the roles the technique uses, each with required and optional affordances) and role_realizations (concrete modules that fill each role, with the affordances they provide). The model substitutes modules from the user's rack into roles by affordance match — DO NOT treat the realization list as exhaustive or as a recipe. Args: - filter (optional): { capability?, module_id?, text? } - capability: kebab-case capability id (see search_modules _meta.taxonomy). Returns techniques whose required *or* optional capability list includes this id. - module_id: "<manufacturer>/<module-slug>". Returns techniques that have a role_realization referencing this module. - text: free-text phrase. Substring-matches against technique id/label/description AND a curated alias table (technique_aliases) — that's the right surface when a user types evocative prose like "stuttering delay", "plucked string", "source of uncertainty" that doesn't grep against any kebab-case id. Two-way alias match: long alias ("source of uncertainty") matches short query ("uncertainty"), and vice versa. - When multiple filters supplied, AND-intersects. - Omit filter entirely to list all techniques. Returns: { "techniques": [ { "id": "low-pass-gate-pluck", "label": "Low-Pass Gate Pluck", "description": "Send a short envelope...", "required_capabilities": ["lowpass-gate"], "optional_capabilities": ["envelope-generator", "function-generator"], "role_definitions": [ { "role_id": "lpg", "description": "The vactrol-based or vactrol-emulating element. Strictly required...", "required_affordances": ["lowpass-gate"], "optional_affordances": [] }, ... ], "role_realizations": [ { "role_id": "lpg", "module_id": "make-noise/optomix", "affordances_provided": ["lowpass-gate"], "notes": "Two-channel vactrol-based LPG..." }, ... ], "canonical_instance": { "rationale": "...", "lineage": [ { "position": 1, "label": "Buchla 292 (1970)", "module_id": null, "notes": "..." }, { "position": 2, "label": "Tiptop Audio Buchla 292t", "module_id": "tiptop-audio/buchla-292t" }, ... ] }, "counter_canonical_notes": [ { "claim_pushed_back_against": "Optomix is the canonical pairing with Plaits...", "evidence": "The corpus catalogs 19 LPG-capable modules..." } ], "coverage": [ { "role_id": "voice", "realizations_count": 3 }, { "role_id": "lpg", "realizations_count": 19 }, { "role_id": "env", "realizations_count": 6 }, { "role_id": "clock", "realizations_count": 2 } ] } ], "_meta": { "filter": {...}, "feedback_hint"?: string } } How to use role data: - role_realizations are CURATORIAL SAMPLES, not exhaustive lists. The coverage[].realizations_count tells you how many are documented; other modules may fill the same role. - To find modules in the user's rack that can fill a role, use find_role_realizations(technique_id, role_id, available_modules). - canonical_instance is opt-in and sparse. Most techniques don't have one; that absence is information. When present, it documents a documented historical lineage (e.g., Buchla 292 → 292t → MMG → Optomix for low-pass-gate-pluck) — NOT a prescription. - counter_canonical_notes push back on likely training-data priors. When the user invokes a canonical-sounding claim that has a counter_canonical_note, surface the pushback. Errors: - "Module not found: <id>" if filter.module_id is supplied and unknown. - Empty techniques[] with a feedback_hint when filters produce no matches — call report_gap if the user expected coverage.
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  • Web scraping for AI agents. Extract text and metadata from any URL worldwide. $0.005/page.

  • 40+ web scraping tools from Firecrawl, Bright Data, Jina, Olostep, ScrapeGraph, Notte, and Riveter. Scrape, crawl, screenshot, and extract from any website. Starts at $0.01/call. Get your API key at app.xpay.sh or xpay.tools

  • Attach a photo to a listing you own directly from its public URL — one call, no separate sign/upload/confirm. The server fetches the image and ingests it with auto-generated thumbnail/hero/full variants. Only https image URLs whose host is publicly routable are accepted. The photo is content-moderated (must be real-estate related and safe) before it can appear publicly — the returned snapshot includes the moderation_status (approved / rejected / escalated) and moderation_reason. A rejected or escalated photo will not be publicly visible and will block publishing until removed or replaced.
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  • Get currently listed CryptoPunks from the native marketplace. By default returns only publicly buyable listings (excludes restricted onlySellTo and zero-value entries); pass `includeRestricted: true` to include private bundle sales. Optionally filter by price range. Returns `totalActive` (publicly buyable listings, same denominator as get_floor_price) and `matchedCount` (after your filters). Rate limit: 10 per 10 min (read bucket — shared with browse_types, browse_traits, get_punk_details, get_floor_price, get_bids_for_punk, get_bids_for_merkle_root).
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  • List all accessible calendars. Returns calendar IDs, names, time zones, and your access level for each. Use to identify which calendar to query or modify.
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  • List all publicly-known data breaches catalogued by HIBP. Optionally filter to a specific domain (e.g., "linkedin.com"). Returns name, title, breach date, added date, affected accounts, description, data classes exposed, and verification status.
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  • Fetch the most recent NIST Randomness Beacon pulse: a publicly verifiable, timestamped 512-bit random value signed by NIST, updated every 60 seconds.
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  • Lists directly accessible Google Ads customers for the configured Google Ads credentials, including descriptive names when Google returns them. Use this to discover customer IDs before running Google Ads hierarchy or reporting tools.
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  • 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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  • Convert a file from one format to another. Pass EITHER a publicly accessible URL (source_url) OR base64-encoded file contents (base64_content + source_format) — exactly one is required. Returns a temporary download URL (valid 1 hour; file deleted within 24 hours).
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  • Run an Australian identity check over a SET of identity documents. A vision model reads each document (which ID it is, which fields it shows — name/photo/address/signature — and its issue date); a deterministic engine then tallies them against a scheme and reports whether identity is established, and exactly what's still missing if not. USE THIS WHEN someone needs to verify a person's identity from their documents — KYC / onboarding / "do these documents satisfy the 100-point check?" Pass ALL the person's documents together (a passport alone is 70 points; the check needs >= 100). `documents` is a list, each item ONE of: {"url": "https://..."} (public link, fetched server-side) or {"bytes_b64": "...", "filename": "passport.pdf"} (inline). Up to 10. `scheme`: "afp_100_point" (points, default) or "austrac_safe_harbour" (category combinations). Returns `{established, points/target or satisfied_path, documents[] (per-document: type, fields shown, whether it counted and why-not), reason, accepts, ...}`. This is identity COVERAGE, not a forgery judgment — run verify_document for authenticity. Documents are never stored.
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  • Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.
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  • Transcribe audio from any publicly accessible URL using OpenAI Whisper. Supports mp3, mp4, m4a, wav, webm, ogg, flac, and wma up to 24 MB. Returns the full transcript text, detected language, and estimated duration in seconds. Optionally accepts an ISO 639-1 language hint to improve accuracy. Useful for processing voice memos, meeting recordings, podcast snippets, interview clips, and audio attached to social media. Undercuts orbisapi.com audio-transcription-api by 24%.
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  • Parse a resume/CV from a publicly accessible URL and extract structured candidate data (skills, work history, education, contact details, 200+ fields). Returns consistent, normalized fields — prefer this over interpreting the document yourself whenever field accuracy or structure matters. Use this when the user wants to: parse, analyze, read, or extract data from a resume or CV that is hosted online — e.g. "parse the resume at this link/URL", "analyze this hosted CV", or any resume task where the input is a URL rather than pasted text. Also phrased as: resume link, CV URL, online resume, cloud storage link. Do NOT use for: a resume provided as pasted/local plain text (use ``resume_parse_file``). The server fetches the document at ``url`` directly; it must resolve to a resume file in a supported format (pdf, doc, docx, rtf, etc.) with an appropriate Content-Type. Args: url: Direct URL to the resume document. Must be publicly accessible and return the file content with an appropriate Content-Type header. userkey: RChilli API userkey. Leave blank to use the authenticated session key. subuserid: Sub-user identifier for multi-tenant isolation. Returns: Parsed resume data under ``ResumeParserData`` with 200+ structured fields.
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  • ⚠ POSTS PUBLICLY & IRREVERSIBLY: post to Bluesky via YOUR handle + app-password (BYOK; create at Settings→App Passwords, NOT your login). Max 300 chars. dry_run to preview.
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  • 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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