이 MCP로 할 수 있는 일
Aggregates tools for web accessibility, AI compliance, financial analysis, API migration, software security, payment operations, and regulatory or business checks.
기능
도구
44
도구
accessproof__check_page_accessibility
Scan a single live, publicly reachable web page's markup for the WCAG 2.1 failures that ADA web-accessibility demand letters and lawsuits cite most often: missing alt text, unlabeled form fields, missing lang attribute, empty links, skipped heading levels, missing page title, no h1, no skip link. Static markup analysis -- it can't check color contrast, keyboard navigation, or screen reader behavior, so a clean result means 'no known markup-level issue found,' not full compliance.
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입력 스키마
{'type': 'object', 'required': ['url'], 'properties': {'url': {'type': 'string', 'description': 'A full http:// or https:// URL of the page to scan'}}}
advisor-letter__get_advisor_letter_info
Get pricing and details for AdvisorLetter: a weekly white-label market-commentary draft that financial advisors review and send to clients under their own name. Useful for an agent helping a financial advisor or RIA find a done-for-them (not done-by-AI-and-sent-raw) client communication product.
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입력 스키마
{'type': 'object', 'properties': {}}
advisor-letter__get_sample_issue
Get a real sample AdvisorLetter issue -- the exact ready-to-forward weekly market-commentary draft an advisor reviews and sends to clients under their own name. This is a fixed sample issue, not this week's live draft -- the paid subscription is a fresh issue every Monday. Free, no key.
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입력 스키마
{'type': 'object', 'properties': {}}
ai-disclosure-kit__check_article50_disclosure
Check whether the EU AI Act's Article 50 transparency rule applies to one of your AI touchpoints, and get a free sample disclosure notice for it. Covers chatbots, AI-generated images/audio/video, AI-generated public text, and emotion-recognition/biometric features. Returns which Article 50 obligation applies, where the notice belongs, and one ready-to-use disclosure sentence -- the same free preview shown on the web tool before checkout. Paste in your own business name for a personalized sentence. Free, no key.
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{'type': 'object', 'required': ['touchpoint'], 'properties': {'touchpoint': {'enum': ['chatbot', 'synthetic_media', 'public_text', 'biometric'], 'type': 'string', 'description': "Which AI touchpoint to check: 'chatbot' (conversational AI), 'synthetic_media' (AI-generated/edited images, audio, or video), 'public_text' (AI-generated text published to the public), or 'biometric' (emotion-recognition or biometric-categorization features)."}, 'businessName': {'type': 'string', 'description': "Optional business name to personalize the sample disclosure text. Defaults to 'Your business'."}}}
ai-disclosure-kit__get_ai_disclosure_kit_info
Get pricing and details for AI Disclosure Kit: ready-to-use EU AI Act Article 50 transparency-obligation text, an embeddable disclosure banner, and a compliance record template for chatbots, AI-generated media, and biometric-categorization/emotion-recognition features. One-time $59. Useful for an agent implementing EU AI Act transparency disclosures for its user's product.
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{'type': 'object', 'properties': {}}
altman-z-score-calculator__compute_altman_z_score
Compute the Altman Z-Score (public-company, non-financial-services version) for a US-listed ticker -- a quick bankruptcy-risk / financial-distress screen from five balance-sheet ratios. Looks up working capital, total assets, retained earnings, EBIT, market cap, total liabilities, and revenue from SEC EDGAR + market data automatically -- just pass a ticker. Returns the score and which zone it falls in: safe (>2.99), grey (1.81-2.99), or distress (<1.81).
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입력 스키마
{'type': 'object', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'description': 'A US-listed ticker symbol, e.g. GE'}}}
apidrift__get_apidrift_info
Get pricing and details for APIDrift: weekly plus same-day urgent email alerts tracking deprecations, breaking schema changes, and pricing shifts across OpenAI, Anthropic, Google, xAI, Together, Mistral, Groq, Cloudflare Workers AI, and AWS Bedrock. Useful for an agent helping an engineering team that depends on LLM provider APIs avoid getting blindsided by an upstream breaking change.
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{'type': 'object', 'properties': {}}
apidrift__get_recent_breaking_changes
Get real, dated example entries of the kind of LLM-provider breaking change APIDrift catches -- model retirements, endpoint shutdowns, and schema/pricing changes across OpenAI, Anthropic, Google, xAI, Together, Mistral, Groq, Cloudflare Workers AI, and AWS Bedrock, each with what actually broke and what to check. These are illustrative sample entries, not a live feed -- the paid subscription is the ongoing weekly digest plus same-day urgent alerts as new changes ship. Free, no key.
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입력 스키마
{'type': 'object', 'properties': {}}
bank-stress-dataset__get_bank_stress_dataset_info
Get details and pricing for the US Bank Regulatory Stress Dataset: a flat CSV covering every FDIC-insured bank's balance-sheet stress metrics (AOCI burden on capital, uninsured deposit ratio, non-performing loan ratio, and core balance-sheet figures) computed directly from each bank's own public FFIEC Call Report. Useful for an agent building a bank-screening or credit-risk model that needs a licensable raw data input instead of scraping regulatory filings itself.
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입력 스키마
{'type': 'object', 'properties': {}}
bank-stress-dataset__lookup_bank_stress_metrics
Look up one US bank's balance-sheet stress metrics, computed from that bank's own FFIEC Call Report and citable as an official-source figure: AOCI burden on capital (how much of equity unrealised securities losses have eaten), uninsured deposit ratio, non-performing loan ratio, total assets and state. Covers all 4,296 FDIC-insured institutions for 2026 Q2 (filed as of 06/30/2026). Use this when an agent needs a grounded answer to "how stressed is this bank?" instead of guessing from memory or reading a filing by hand. Free, no key. One institution per call.
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입력 스키마
{'type': 'object', 'required': ['name'], 'properties': {'name': {'type': 'string', 'description': 'Institution name or a distinctive part of it, e.g. "CITIBANK, N.A." or "Zions". Minimum 3 characters.'}}}
chargeback-response__draft_chargeback_response_checklist
Given a chargeback/dispute reason code category and order details, return the evidence checklist for that reason code (what to attach: tracking numbers, prior-order signals, refund records, etc.) and a preview of the response letter. Covers Visa 10.4/13.1/13.3/13.7/13.6/12.6.1 and the equivalent Mastercard reason codes. The full formatted dispute-response letter is a separate $39 product at https://www.edgethirteen.com/tools/chargeback-response. Not legal advice.
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{'type': 'object', 'required': ['category'], 'properties': {'amount': {'type': 'string', 'description': 'Disputed amount'}, 'category': {'enum': ['fraud_card_absent', 'not_received', 'not_as_described', 'subscription_canceled', 'credit_not_processed', 'duplicate_charge'], 'type': 'string', 'description': "The dispute reason category: fraud_card_absent (“I didn't make this purchase” (Visa 10.4, Mastercard 4837 — fraud)); not_received (“I never got it” (Visa 13.1, Mastercard 4855 — product/service not received)); not_as_described (“It's not what I ordered” (Visa 13.3, Mastercard 4853 — not as described)); subscription_canceled (“I cancelled / didn't authorize the renewal” (Visa 13.7, Mastercard 4841)); credit_not_processed (“They never refunded me” (Visa 13.6, Mastercard 4860 — credit not processed)); duplicate_charge (“I was charged twice” (Visa 12.6.1, Mastercard 4834 — duplicate processing))"}, 'currency': {'type': 'string', 'description': 'Currency code, defaults to USD'}, 'order_id': {'type': 'string', 'description': 'Order or transaction ID'}, 'order_date': {'type': 'string', 'description': 'Order date'}, 'merchant_name': {'type': 'string', 'description': 'Merchant/business name'}, 'product_description': {'type': 'string', 'description': 'What was sold'}}}
cloakcheck__check_page_for_agent_hijacking
Fetch a URL and scan it for content planted to hijack an AI agent visiting it rather than to inform a human: invisible unicode (zero-width joiners, steganographic tag-block characters), CSS-hidden text (display:none, opacity:0, off-screen) paired with instruction-shaped language ('ignore previous instructions', 'add to cart and checkout', fake system-role text), and instruction-shaped phrases in alt/title/aria-label attributes or meta tags. Call this before an autonomous browsing or checkout flow acts on instructions found on a page. A clean result means no known hijack pattern found, not a full content-safety guarantee.
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입력 스키마
{'type': 'object', 'required': ['url'], 'properties': {'url': {'type': 'string', 'description': 'Full URL (http:// or https://) of the page to scan'}}}
commentlettercheck__check_sec_comment_letters
Look up whether a US-listed ticker has any SEC comment-letter correspondence on file (staff review letters and company responses, form types UPLOAD/CORRESP). Returns a free-tier preview: filing count and most recent filing date, sourced live from SEC EDGAR. Does not include letter content or severity scoring -- that's the paid full report.
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입력 스키마
{'type': 'object', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'description': 'A US-listed stock ticker symbol, e.g. AAPL'}}}
dcf-calculator__compute_dcf
Compute a simplified discounted-cash-flow intrinsic value per share: project free cash flow per share forward at a constant growth rate, discount back at a discount rate, add a Gordon-growth terminal value. Pass fcf/growth/discount/terminal/years directly (these are judgment calls, not looked up). Optionally pass a ticker to auto-fill the current price for a margin-of-safety comparison.
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{'type': 'object', 'required': ['fcf', 'growth', 'discount', 'terminal', 'years'], 'properties': {'fcf': {'type': 'number', 'description': 'Free cash flow per share'}, 'price': {'type': 'number', 'description': 'Current price, used instead of a ticker lookup'}, 'years': {'type': 'number', 'description': 'Number of projection years, e.g. 10'}, 'growth': {'type': 'number', 'description': 'Growth rate for the projection years, in percent, e.g. 8'}, 'ticker': {'type': 'string', 'description': 'Optional ticker, used only to fetch the current price'}, 'discount': {'type': 'number', 'description': 'Discount rate, in percent, e.g. 10'}, 'terminal': {'type': 'number', 'description': 'Terminal growth rate, in percent, e.g. 2.5'}}}
drop-compliance-kit__check_drop_next_deadline
Given a California data broker's DROP registration/start date, return the next 45-day DROP (Delete Request and Opt-out Platform) check-in deadline and the first two items of the compliance checklist. Missing a cycle costs $200/day per unprocessed deletion request, required starting August 1, 2026. The full 20-cycle calendar file, deletion-log template, and complete checklist are a separate $49 product at https://www.edgethirteen.com/tools/drop-compliance-kit. Not legal advice.
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{'type': 'object', 'required': ['registration_date'], 'properties': {'business_name': {'type': 'string', 'description': 'Business name'}, 'registration_date': {'type': 'string', 'description': 'Data broker registration date (or today, if unsure), YYYY-MM-DD'}}}
exploitwatch__check_dependencies_against_kev
Check a comma-separated list of software dependency/product names against CISA's live Known Exploited Vulnerabilities (KEV) catalog. Returns any matches with the CVE, vulnerability name, and why it matched. Call this before shipping or during a dependency/security review to catch actively-exploited components, or when working out whether an EU Cyber Resilience Act Article 14 reporting obligation (the 24h early warning / 72h notification / 14-day final report clock) has been triggered. Matching is by name and deliberately errs towards over-matching, so review each hit before acting on it.
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{'type': 'object', 'required': ['dependencies'], 'properties': {'dependencies': {'type': 'string', 'description': 'Comma-separated dependency/product names, e.g. "express, lodash, openssl"'}}}
graham-number-calculator__compute_graham_number
Compute Benjamin Graham's fair-value ceiling (sqrt(22.5 * EPS * book value per share)) for a US-listed ticker, and the margin of safety against its current price. Looks up EPS, book value per share, and price from SEC EDGAR + market data automatically -- just pass a ticker. You can also pass eps/bvps/price directly to compute it for a hypothetical company with no ticker.
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{'type': 'object', 'properties': {'eps': {'type': 'number', 'description': 'Earnings per share, used instead of a ticker lookup'}, 'bvps': {'type': 'number', 'description': 'Book value per share, used instead of a ticker lookup'}, 'price': {'type': 'number', 'description': 'Current price, used to compute margin of safety'}, 'ticker': {'type': 'string', 'description': 'A US-listed ticker symbol, e.g. AAPL'}}}
hubspot-dbv__get_hubspot_dbv_info
Get background and pricing for the HubSpot legacy-to-date-based-versioning (DBV) migration map: what's going unsupported, when, and where the full free map and $29/mo DBV Watch monitoring live. Useful for an agent helping a developer or agency plan a HubSpot API migration off v1-v4 before HubSpot's own per-endpoint docs ship in March 2027.
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{'type': 'object', 'properties': {}}
hubspot-dbv__list_hubspot_breaking_changes
List HubSpot API operations whose date-based-versioning replacement is BREAKING (a caller-visible field or parameter difference) or REMOVED (no date-based counterpart exists at all), optionally filtered by API name (e.g. 'CRM', 'Webhooks'). Useful for scoping how big a given migration is before starting it.
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입력 스키마
{'type': 'object', 'properties': {'api': {'type': 'string', 'description': "Optional substring filter on the HubSpot API name, e.g. 'webhooks'."}}}
hubspot-dbv__lookup_hubspot_endpoint
Look up a legacy HubSpot API path (e.g. '/crm/v3/objects/contacts' or just 'contacts') and get its date-based-versioning replacement, whether the change is breaking, and the exact field-level differences (removed params, newly-required fields, changed types). Derived by diffing HubSpot's own public OpenAPI specs -- not a guess. Free, no key, full data (this map has no paid tier gating it).
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{'type': 'object', 'required': ['path'], 'properties': {'path': {'type': 'string', 'description': "A legacy HubSpot API path or fragment, e.g. '/crm/v3/objects/contacts' or 'contacts'."}, 'method': {'type': 'string', 'description': 'Optional HTTP method filter, e.g. GET, POST.'}}}
industry-primers__get_industry_primer_info
Get details and pricing for Edge Thirteen's current Industry Primer report: a one-time research report on a single investable industry theme, with real revenue/margin/growth figures pulled from each covered company's own SEC 10-K (not modeled or estimated), plus the analytical read on industry structure and competitive positioning. Useful for an agent helping with investment research that needs a sourced industry-level writeup instead of an LLM-generated summary.
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{'type': 'object', 'properties': {}}
industry-primers__get_primer_preview_table
Get the free FY2025 preview table from Edge Thirteen's current Industry Primer: ticker, FY2025 revenue, YoY growth, gross margin, and net margin for each covered company, sourced to that company's own 10-K via SEC EDGAR's XBRL company-facts API. This is the same free table already on the tool page -- the paid report adds FY2023-FY2024 comparatives, exact XBRL tag/accession sourcing per figure, and the written analysis. Free, no key.
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{'type': 'object', 'properties': {}}
kdpcheck__check_manuscript_for_ai_slop_patterns
Analyze manuscript text for patterns associated with AI-generated prose: cliche-phrase density, unnaturally uniform sentence-length rhythm, repeated paragraph openers, and overused transition words. Returns a 0-100 score, a high/medium/low band, and the single most severe flag -- the full flag breakdown with fix guidance for every flag is the paid $29 report at https://www.edgethirteen.com/tools/kdpcheck. Not a claim about authorship, just a pattern scan a writer can use to self-edit before publishing.
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{'type': 'object', 'required': ['text'], 'properties': {'text': {'type': 'string', 'description': 'The manuscript or excerpt text to analyze (longer excerpts score more reliably)'}}}
killcord__get_killcord
Get the killcord script: a dead-man's switch for Anthropic API spend. Self-hosted, dependency-free Node script that polls Anthropic's real Admin Usage & Cost API and deactivates the API key the instant spend crosses a limit -- for stopping a runaway agent loop, not just alerting on it. Returns the full script source plus a ready-to-run setup snippet, optionally pre-filled with the workspace/limit/keys you provide, so it can be written straight into the project being worked on.
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{'type': 'object', 'properties': {'keys': {'type': 'string', 'description': 'Comma-separated Anthropic API key IDs to deactivate when tripped, e.g. apikey_...'}, 'limitUsd': {'type': 'number', 'description': 'Spend threshold in USD that trips the kill switch'}, 'webhookUrl': {'type': 'string', 'description': 'Optional webhook URL to notify on trip/reset'}, 'workspaceId': {'type': 'string', 'description': 'Anthropic Workspace ID to watch, e.g. wrkspc_...'}}}
meterkit__get_meterkit_bug_fix_sample
Get a free, real code sample from MeterKit: the fix for a common Stripe webhook bug where access is only revoked on customer.subscription.deleted, missing that a card decline usually transitions a subscription via .updated first (sometimes without .deleted ever firing). This is the same free sample already on the tool page -- the paid kit is the surrounding webhook route plus the event-sourced credit ledger and Meter Events reporting/reconciliation, which this sample does not include. Free, no key.
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입력 스키마
{'type': 'object', 'properties': {}}
meterkit__get_meterkit_info
Get pricing and details for MeterKit: a drop-in, event-sourced credit ledger plus a correct 2026 Stripe Billing Meter Events API integration for Next.js AI/SaaS products (the old usage_type: "metered" price approach was retired as of Stripe API version 2025-03-31.basil). Zero runtime dependencies, one-time $99, buyer owns the code. Useful for an agent implementing Stripe usage-based billing for its user.
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입력 스키마
{'type': 'object', 'properties': {}}
numbercheck__check_financial_numbers
Check $CASHTAG-style ticker mentions (e.g. $AAPL) in a piece of financial writing against SEC EDGAR's own XBRL company-facts data for that company's most recent 10-K -- EPS, book value per share, revenue, market cap, total assets, total liabilities. Flags numeric claims that don't match the filed figures.
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{'type': 'object', 'required': ['text'], 'properties': {'text': {'type': 'string', 'description': 'The draft text to check, with $TICKER cashtags for each company mentioned.'}}}
postingcheck__check_job_posting_pay_transparency
Scan a job posting's text against the free-preview subset of US state salary-range-disclosure laws (CA, CO, NY, WA) and flag exactly which required element (salary range, benefits description) is detectably missing, with the statute citation. The full 15-state + DC report (CT, HI, IL, MD, MA, MN, NV, NJ, RI, VT, VA, DC too) is a separate $49 report at https://www.edgethirteen.com/tools/postingcheck. Conservative: never certifies a posting as compliant, only flags what's missing. Not legal advice.
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입력 스키마
{'type': 'object', 'required': ['posting_text'], 'properties': {'posting_text': {'type': 'string', 'description': 'The full text of the job posting'}, 'employee_count': {'type': 'number', 'description': "Employer's total employee count, used for laws with a minimum-employee threshold (optional)"}}}
pumpcheck__check_npm_download_trust
Check whether an npm package's public download count reflects real adoption. Detects 'download pumping' -- the documented supply-chain technique where a package is published in hundreds of rapid-fire versions so registry mirrors and security scanners inflate its download counter, making an unused or malicious package look popular. Returns npm's headline 30-day count, a spike-resistant estimate of sustained real usage, the share of the month falling on the busiest single day, recent version-flood bursts, and a verdict of clean, unreliable or inflated. Use before adding or recommending a dependency, especially a new or unfamiliar one.
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{'type': 'object', 'required': ['package'], 'properties': {'package': {'type': 'string', 'description': 'The npm package name, e.g. express or @upstash/context7-mcp.'}}}
renewal-matrix__check_renewal_cancellation_compliance
Score a subscription business's signup/cancellation flow against US click-to-cancel and auto-renewal law (federal FTC Section 5/ROSCA, plus California AB 2863, Colorado SB25-145, Vermont, and Oregon). Returns the federal-level result now; the full state-by-state breakdown with statute citations is a separate $49 report at https://www.edgethirteen.com/tools/renewal-matrix. Not legal advice.
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{'type': 'object', 'required': ['sells_states', 'online_cancel'], 'properties': {'sells_states': {'type': 'string', 'description': "Comma-separated state codes the business sells to, or 'nationwide'"}, 'online_cancel': {'type': 'boolean', 'description': 'Can a customer cancel online, in the same medium used to sign up?'}, 'online_signup': {'type': 'boolean', 'description': 'Can a customer sign up online?'}, 'prechecked_consent': {'type': 'boolean', 'description': 'Is the auto-renewal consent box pre-checked by default?'}, 'renewal_notice_days': {'type': 'number', 'description': 'Days of advance notice given before a renewal charge, if any'}, 'b2b_customers_colorado': {'type': 'boolean', 'description': 'Does the business have B2B customers in Colorado?'}, 'phone_or_email_required': {'type': 'boolean', 'description': 'Is a phone call or email required to cancel?'}, 'long_term_or_discounted_trial': {'type': 'boolean', 'description': 'Is this a 1+ year term, or a discounted/free trial converting to full price?'}}}
rewardsguard__check_tiktok_rewards_risk
Spot-check a TikTok creator's exported video list for TikTok Creator Rewards Program disqualification-risk signals: repetitive/duplicate captions, unnaturally regular posting cadence, ineligible formats (duet/stitch/photo), and under-duration videos. Returns a 0-100 risk score, a band (low/medium/high), and the single highest-severity flag -- the full flag breakdown is the paid product at edgethirteen.com/tools/rewards-guard. Input is the same caption/postedAt/durationSeconds/format rows TikTok Studio's own analytics export gives a creator about their own account.
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{'type': 'object', 'required': ['videos'], 'properties': {'videos': {'type': 'array', 'items': {'type': 'object', 'required': ['caption', 'postedAt', 'format'], 'properties': {'format': {'type': 'string', 'description': 'video | duet | stitch | photo'}, 'caption': {'type': 'string'}, 'postedAt': {'type': 'string', 'description': 'ISO date or datetime'}, 'durationSeconds': {'type': ['number', 'null']}}}, 'description': "1-60 rows of the creator's own video data"}}}
sanctions__screen_name
Screen a person or company name against OFAC's SDN and Consolidated Sanctions lists (19,874 entities, 21,320 aliases) via SanctionRail, for an agent checking a counterparty before a transaction, vendor onboarding, or payment approval. Returns fuzzy matches banded exact/strong/probable/weak with the sanctions programme, source list, and a common-name-collision flag so a common name like 'Maria Garcia' is surfaced, not silently suppressed. Free tier: 25 lookups/day per caller IP, no key required.
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{'type': 'object', 'required': ['name'], 'properties': {'name': {'type': 'string', 'description': 'Person or company name to screen.'}}}
site-audit__audit_site_accessibility_and_agent_safety
Discover a website's pages from its sitemap (or a homepage crawl as fallback) and sweep a free sample through two engines: WCAG 2.1 accessibility checks and AI-agent prompt-injection checks. Returns how many pages exist, how many were sampled, severity counts, and which categories of problem were found -- not the finding text or which page it's on. Call this before launch or handoff to catch site-wide accessibility and agent-hijacking exposure a single-page scan would miss. The full 40-page report with exact locations and a worst-first remediation order is a separate $499 product at https://www.edgethirteen.com/tools/site-audit.
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입력 스키마
{'type': 'object', 'required': ['site'], 'properties': {'site': {'type': 'string', 'description': 'A website address, e.g. example.com'}}}
slopcheck__check_youtube_channel_slop_risk
Check a YouTube channel's recent uploads against YouTube's 2026 inauthentic-content ('AI slop') policy: title/description repetition, upload-cadence regularity, and AI-disclosure language. Returns an overall risk band (low/medium/high), a numeric score, and the single most severe flag found. This is a heuristic proxy for YouTube's own review process, not a simulation of it. The full flag-by-flag report with exact numbers and suggested fixes is a separate paid product at https://www.edgethirteen.com/tools/slopcheck.
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입력 스키마
{'type': 'object', 'required': ['channel'], 'properties': {'channel': {'type': 'string', 'description': 'YouTube channel handle (e.g. @somechannel), URL, or channel ID'}}}
stackledger__audit_saas_subscriptions
Get an instant monthly/annual spend total for a pasted list of SaaS subscriptions, one per line as 'Name, monthly cost, category' (category is optional -- common tools like Slack or Notion are auto-recognized), plus a count of categories with likely overlap (e.g. two project-management tools). This is the free-tier preview -- the per-category breakdown, which line items are priced high for their category, and a consolidation-savings estimate are the $49 paid report at https://www.edgethirteen.com/tools/stackledger.
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{'type': 'object', 'required': ['subscriptions'], 'properties': {'subscriptions': {'type': 'string', 'description': 'One subscription per line as "Name, cost[, category]", e.g. "Notion, 10\\nAsana, 13\\nSlack, 8.75"'}}}
tariff-refund-screen__get_tariff_refund_screen_info
Get details and pricing for Edge Thirteen's Tariff Refund Screen: a one-time CSV of US-listed companies disclosing IEEPA tariff-refund figures in their own SEC 10-Q/10-K filings since the Supreme Court struck down IEEPA tariff authority. These dollar figures are gain contingencies under ASC 450-30, so they carry no XBRL tag and don't appear on any stock screener -- they exist only as footnote prose. Useful for an agent doing investment research that needs to find a disclosure no numeric screen can surface.
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입력 스키마
{'type': 'object', 'properties': {}}
tariff-refund-screen__get_tariff_refund_screen_preview
Get the free top-10 preview from the Tariff Refund Screen: ticker, company, disclosed amount, whether it's paid/accepted/received, and IEEPA refund as a percentage of shareholders' equity, ranked by materiality. This is the same free table already on the tool page -- the paid CSV adds the other 150 cited companies plus the exact citation sentence and filing URL for every figure. Free, no key.
읽기 전용
입력 스키마
{'type': 'object', 'properties': {}}
triageshield__verify_vulnerability_report
Check a vulnerability report's concrete claims (file paths, file:line references, function names) against a real public GitHub repo's current contents. Flags claims that don't check out -- the file doesn't exist, the line is past EOF, the function isn't in the file -- which is the most common signature of an AI-generated fabricated vuln report. Does not judge whether a real, verifiable claim describes an actual security bug; it only checks whether the claim is honest about the codebase.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'required': ['repo', 'report'], 'properties': {'repo': {'type': 'string', 'description': 'A github.com/owner/name URL for the public repo being reported against'}, 'report': {'type': 'string', 'description': 'The full text of the vulnerability report to check'}}}
us-diligence__screen_us_company
Due diligence on a US company, from official federal records. Screens a company name against SEC EDGAR (is it a registered filer, under what CIK, state of incorporation and SIC code), the US Treasury OFAC SDN sanctions list, USAspending.gov federal contract and grant awards, and federal court dockets via CourtListener/RECAP. Use before onboarding a vendor, signing a supplier, screening a counterparty or qualifying a sales lead. Free screen returns how many records each source holds plus one sample record each; sources that cannot be reached are reported as not-checked rather than as clean.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'required': ['name'], 'properties': {'name': {'type': 'string', 'description': 'The US company\'s legal name, e.g. "Palantir Technologies Inc."'}}}
valuefeed__get_sample_screen
Get a real sample run of ValueFeed's Graham/Buffett-style value screen: per-name metrics (P/E, P/B, Graham fair value, margin of safety, ROE, current ratio, debt/equity, yield, years of positive EPS) for two names, plus an SEC 10-K/10-Q filing excerpt for one of them. This is a fixed illustrative sample, not a live run across the whole market -- the paid subscription is a fresh weekly screen every Monday. Free, no key.
읽기 전용
입력 스키마
{'type': 'object', 'properties': {}}
valuefeed__get_valuefeed_info
Get pricing and details for ValueFeed: a weekly SEC-sourced value-investing research packet (screens, metrics, filing excerpts) licensed for independent newsletter writers and content creators to build their own commentary on top of. Useful for an agent helping a finance content creator find raw research inputs instead of raw LLM-generated numbers.
읽기 전용
입력 스키마
{'type': 'object', 'properties': {}}
vercelpycheck__check_vercel_python_project
Scan pasted project files for known Vercel Python-runtime deploy footguns: conflicting requirements.txt/pyproject.toml manifests, a dependency manifest missing from the project root, sibling-module imports that need sys.path, multiple top-level ASGI apps under api/, streaming/SSE responses that can crash the Python runtime, oversized dependencies (torch/tensorflow/etc.), and unrouted .well-known/ files. Static analysis over file contents -- it doesn't run a real build, so a clean result means 'no known footgun found,' not a deploy guarantee. To scan a public GitHub repo automatically instead of pasting files, use the $29 checkout at https://www.edgethirteen.com/tools/vercelpycheck.
읽기 전용
입력 스키마
{'type': 'object', 'required': ['files'], 'properties': {'files': {'type': 'string', 'description': "Project files bundled as repeated '### FILE: path' markers followed by that file's content, e.g. '### FILE: requirements.txt\\nfastapi\\n### FILE: api/index.py\\n...'. Include api/*.py files plus root manifests (requirements.txt, pyproject.toml, vercel.json, uv.lock)."}}}
voicebrief__get_stock_metric
Answer one financial metric for a US public company, spoken as a single natural-language sentence grounded in that company's most recent SEC 10-K filing (via EDGAR's XBRL data) -- not a guess. Use for a specific spoken question like "what's Tesla's revenue" or "what's Apple's earnings per share". Metric must be one of: revenue, eps, book_value_per_share, market_cap, total_assets, total_liabilities, price.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'required': ['company', 'metric'], 'properties': {'metric': {'enum': ['revenue', 'eps', 'book_value_per_share', 'market_cap', 'total_assets', 'total_liabilities', 'price'], 'type': 'string', 'description': 'Which figure to report.'}, 'company': {'type': 'string', 'description': 'Company name or ticker, e.g. "Apple" or "AAPL".'}}}
voicebrief__get_stock_snapshot
Give a short spoken financial snapshot of a US public company (revenue, earnings per share, market cap, book value per share) grounded in its most recent SEC 10-K filing. Use for a broad spoken question like "tell me about Apple's financials" rather than one specific figure.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'required': ['company'], 'properties': {'company': {'type': 'string', 'description': 'Company name or ticker, e.g. "Apple" or "AAPL".'}}}
기록
최근 도구 변경
추가됨
sanctions__screen_name
2026년 9월 20일 2:40 AM
추가됨
vercelpycheck__check_vercel_python_project
2026년 9월 18일 2:40 AM
추가됨
valuefeed__get_sample_screen
2026년 9월 18일 2:40 AM
추가됨
valuefeed__get_valuefeed_info
2026년 9월 18일 2:40 AM
추가됨
voicebrief__get_stock_snapshot
2026년 9월 18일 2:40 AM
추가됨
voicebrief__get_stock_metric
2026년 9월 18일 2:40 AM
추가됨
us-diligence__screen_us_company
2026년 9월 18일 2:40 AM
추가됨
triageshield__verify_vulnerability_report
2026년 9월 18일 2:40 AM
추가됨
stackledger__audit_saas_subscriptions
2026년 9월 18일 2:40 AM
추가됨
slopcheck__check_youtube_channel_slop_risk
2026년 9월 18일 2:40 AM
추가됨
site-audit__audit_site_accessibility_and_agent_safety
2026년 9월 18일 2:40 AM
추가됨
rewardsguard__check_tiktok_rewards_risk
2026년 9월 18일 2:40 AM
추가됨
renewal-matrix__check_renewal_cancellation_compliance
2026년 9월 18일 2:40 AM
추가됨
pumpcheck__check_npm_download_trust
2026년 9월 18일 2:40 AM
추가됨
postingcheck__check_job_posting_pay_transparency
2026년 9월 18일 2:40 AM
추가됨
numbercheck__check_financial_numbers
2026년 9월 18일 2:40 AM
추가됨
meterkit__get_meterkit_bug_fix_sample
2026년 9월 18일 2:40 AM
추가됨
meterkit__get_meterkit_info
2026년 9월 18일 2:40 AM
추가됨
killcord__get_killcord
2026년 9월 18일 2:40 AM
추가됨
kdpcheck__check_manuscript_for_ai_slop_patterns
2026년 9월 18일 2:40 AM
추가됨
tariff-refund-screen__get_tariff_refund_screen_preview
2026년 9월 18일 2:40 AM
추가됨
tariff-refund-screen__get_tariff_refund_screen_info
2026년 9월 18일 2:40 AM
추가됨
industry-primers__get_primer_preview_table
2026년 9월 18일 2:40 AM
추가됨
industry-primers__get_industry_primer_info
2026년 9월 18일 2:40 AM
추가됨
graham-number-calculator__compute_graham_number
2026년 9월 18일 2:40 AM
추가됨
exploitwatch__check_dependencies_against_kev
2026년 9월 18일 2:40 AM
추가됨
drop-compliance-kit__check_drop_next_deadline
2026년 9월 18일 2:40 AM
추가됨
dcf-calculator__compute_dcf
2026년 9월 18일 2:40 AM
추가됨
commentlettercheck__check_sec_comment_letters
2026년 9월 18일 2:40 AM
추가됨
cloakcheck__check_page_for_agent_hijacking
2026년 9월 18일 2:40 AM
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