com.stratalize/healthcare · v1.2.1 · crypto-web3
Stratalize Healthcare is healthy: it completed an MCP handshake in 2154 ms and exposes 201 tools.
Retired. Use com.stratalize/stratalize.
Endpoint: https://www.stratalize.com/api/mcp-public?vertical=healthcare (streamable-http)
No repository listed · Website · JSON · Add to my inventory
| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 201 |
| Latency | 2154 ms |
| Last checked (UTC) | 2026-10-14T22:05:45.409Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-14T22:05:45.409Z | Healthy | 2154 |
get_verify_crypto_price | Verify current crypto asset price via multi-source consensus. Returns attested consensus price with agreement score across independent sources (CoinGecko, Coinbase, Kraken). $0.50 USDC per call. |
get_resolve_price_threshold | Resolve whether a crypto asset is above or below a threshold via multi-source consensus for settlement and verification workflows. $0.50 USDC per call. |
get_verify_game_outcome | Multi-source sports game outcome verification with cryptographic receipt. Queries independent data providers, reaches consensus on final score and winner, returns ML-DSA-65 signed receipt anchored on Base. Use when a prediction market or betting agent needs trustless proof of a game result for dispu |
get_resolve_game_outcome | Binary prediction market resolver for sports outcomes. Evaluates home_win, away_win, draw, or not_draw conditions via multi-source consensus. Returns boolean resolution with ML-DSA-65 signed receipt verifiable on Base, designed for autonomous on-chain settlement. Supports NFL, NBA, MLB, NHL, Soccer, |
get_sports_nba_scores | Live NBA scores, game status, and results for the past 7 days and next 7 days. Returns home/away teams, scores, game status (live, final, upcoming), and league/season context. Source: TheSportsDB. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.co |
get_sports_nfl_scores | Live NFL game scores, game status, and results for the past 7 days and next 7 days. Returns teams, scores, and game status. Source: TheSportsDB. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify. $0.02 USDC per call. |
get_sports_mlb_scores | Live MLB game scores and results for the past 7 days and next 7 days. Returns teams, scores, and game status. Source: TheSportsDB. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify. $0.02 USDC per call. |
get_sports_nhl_scores | Live NHL game scores, game status, and results for the past 7 days and next 7 days. Returns teams, scores, and game status. Source: TheSportsDB. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify. $0.02 USDC per call. |
get_sports_scores_multi | Cross-sport intelligence brief — live and recent scores across all active leagues (NBA, NFL, MLB, NHL) in a single attested call. Returns only leagues with recent activity. Use when an agent needs sports context without knowing which leagues are in season. Source: TheSportsDB. Cryptographically atte |
get_web_research_synthesis | Governed web research synthesis with cryptographic receipt. Agent submits a research question; returns an AI synthesis across live web sources with every source domain bound into an ML-DSA-65 signed receipt anchored on Base. $1.00 USDC per call. |
get_regulatory_news_synthesis | Real-time regulatory news synthesis for a topic or agency (SEC, FTC, OCC, CFPB, FDA). Returns current enforcement and rule-change developments synthesized from live sources with a signed receipt proving which sources were consulted. $1.00 USDC per call. |
get_company_intelligence_synthesis | Live company intelligence synthesis: recent litigation, regulatory exposure, financial and news developments for a named company with ML-DSA-65 signed receipt for due diligence workflows. $1.00 USDC per call. |
get_competitive_landscape_synthesis | Competitive landscape synthesis for a market category: current leaders, positioning, and dynamics synthesized from live web sources with a signed provenance receipt. $1.00 USDC per call. |
get_legislative_intelligence_synthesis | Legislative intelligence synthesis: current bill status, recent passages, and amendments for a topic and jurisdiction, synthesized from live sources with a cryptographic receipt. $1.00 USDC per call. |
get_vendor_market_rate | Use when a CFO or procurement team needs to know if they are overpaying for any software vendor. Returns monthly_median, monthly_low, monthly_high, annual_median, pricing_model, source, and data_as_of from healthcare vendor benchmark lookups with Stratalize composite medians as fallback when no vend |
get_category_spend_benchmark | Use when benchmarking total spend in a software category against same-size peers. Returns median monthly spend, p25/p75 band, and sample size for any software category by company size. Example: Mid-market CRM spend median ~$3,500/mo, p75 of $4,900 — organizations above p75 have a negotiation mandate |
get_vendor_negotiation_intelligence | Use when preparing to renew or renegotiate a SaaS contract. Returns typical discount percentage, best negotiation windows, leverage points, auto-renewal risk flags, and a negotiation script for any vendor. Example: Salesforce renewals average 12-18% discount when initiated 90 days before renewal wit |
get_top_vendors_by_category | Use when building a vendor shortlist for a new software category purchase. Returns vendors ranked by mention count and median spend from enterprise spend data. Example: HR tech category — Workday median $42K/mo, BambooHR $3,200/mo, Rippling $8,400/mo — 13x spend spread between enterprise and SMB con |
get_vendor_alternatives | Use when evaluating a vendor switch or building a competitive RFP against an incumbent. Returns alternative vendors with migration complexity scores, estimated savings, and switching narrative. Example: Salesforce alternatives — HubSpot at 22% lower median spend with comparable CRM coverage, Pipedri |
get_saas_negotiation_playbook | Use when a major SaaS contract is approaching renewal or auto-renewal risk. Returns timing strategy, leverage points, walk-away alternatives, and a complete negotiation script for any vendor. Example: Datadog renewal — initiate 90 days before, cite Grafana Cloud at 40% lower cost as walk-away, targe |
get_industry_spend_profile | Use when sizing a technology budget for a specific industry and headcount, or identifying category spend outliers. Returns spend bands, category ranges, and outlier flags scaled to employee count. Example: 500-person healthcare org — total SaaS stack median $1.2M/yr, EHR 34% of spend, clinical produ |
get_vendor_contract_intelligence | Use when reviewing a new vendor agreement or benchmarking contract terms before a negotiation. Returns typical contract length, auto-renewal notice window, price escalation percentage, and key risk clauses for any major vendor. Example: Salesforce standard — 36-month term, 60-day auto-renewal notice |
get_spend_by_company_size | Use when benchmarking software category spend against same-size organizations before a purchase or renewal. Returns SMB, mid-market, and enterprise median monthly spend for any software category. Example: CRM median spend — SMB $1,200/mo, mid-market $8,400/mo, enterprise $42,000/mo — 35x spread conf |
get_software_pricing_intelligence | Use when evaluating a new software purchase or reviewing a vendor quote for hidden costs. Returns common pricing models, hidden cost patterns, implementation cost ranges, and budget guidance by category. Example: CRM hidden costs — API overage $0.02/call adds $8,400/yr at 420K monthly calls, sandbox |
get_category_ai_leaders | Use when assessing brand visibility in AI-generated recommendations or researching which vendors dominate AI platform responses in a software category. Returns vendors ranked by unprompted AI mention frequency. Example: CRM category — Salesforce 42 mentions across 100 queries, HubSpot 28, Microsoft |
get_platform_divergence | Use when identifying gaps between AI platform recommendations and actual market position for a vendor or topic. Returns platform agreement score showing consistency across AI platforms. Example: Salesforce scores 0.91 agreement across ChatGPT, Claude, Gemini, Perplexity — near-universal consensus. N |
get_brand_momentum | Use when monitoring a vendor brand trajectory in AI recommendations or tracking week-over-week competitor momentum for a CMO brief. Returns 4-week momentum score, trend direction, and weekly movement series. Example: HubSpot 4-week momentum +1.8, GROWING trend — 3 consecutive weeks of citation incre |
get_ai_consensus_on_topic | Use when researching how AI systems characterize a vendor, category, trend, or business topic across multiple platforms simultaneously. Returns consensus score, sentiment mix, key themes, and platform-by-platform breakdown. Example: AI in healthcare scores 0.78 consensus — key themes: clinical decis |
get_cms_facility_benchmark | Use when benchmarking hospital operating costs against CMS peer cohort or preparing a healthcare CFO board presentation. Returns peer_group context, benchmark_percentiles, metadata, source attribution, and optional database_row detail from the matched CMS benchmark row by bed size, state, and hospit |
get_payer_intelligence | Use when benchmarking payer performance, building a denial management strategy, or preparing revenue cycle board reporting. Returns denial rates by payer, prior authorization burden by specialty, and payer mix commentary. Example: Commercial payer denial rates — UnitedHealth 8.2%, Cigna 9.4%, Aetna |
get_cms_star_rating | Use when advising on CMS Hospital Star Rating strategy or benchmarking a hospital quality performance trajectory. Returns domain weights, national distribution benchmarks, and improvement priorities. Example: Mortality domain weighted at 22% of overall star — hospitals moving 3 to 4 stars typically |
get_pharmacy_spend_benchmark | Use when benchmarking hospital pharmacy costs or building a pharmacy cost reduction strategy for a board presentation. Returns drug cost per adjusted patient day, 340B savings opportunity from published savings ranges, specialty drug drivers, and GPO targets by bed size. Example: 250-bed community h |
get_nadac_drug_benchmark | Use when a pharmacy buyer, 340B program manager, or CFO agent needs CMS NADAC drug acquisition cost benchmarks for contract negotiation or payer comparison. Returns latest NADAC per unit, effective_date, as_of_date, pricing_unit, ndc_description, normalized ndc11, source ndc, and restatement_detecte |
get_cost_plus_price | Use when a patient, benefits manager, or procurement agent needs Mark Cuban Cost Plus Drugs transparent retail pricing for a specific NDC. Returns medication_name, brand_name, form, unit_price and unit_billing_price labeled transparent retail price estimate (cost+15% model), optional quantity quote, |
get_drug_recall_status | Use when a pharmacy, supply chain, or compliance agent needs FDA drug recall status for an NDC or drug name. Returns recall records (status, classification, reason, dates), match_confidence (ndc_exact or name_match), normalized ndc11, and openFDA provenance — never silently returning a different pro |
get_billing_coding_risk | Use when assessing coding compliance risk before an OIG audit, preparing for a RAC review, or building a revenue integrity program. Returns E/M distribution benchmarks, upcoding risk signals, OIG audit priority themes, and RAC watchlist. Example: Cardiology practice E/M mix at 67% level 4/5 visits v |
get_value_based_care_performance | Use when benchmarking VBC contract performance, assessing FFS-to-VBC transition readiness, or preparing a population health strategy presentation. Returns MSSP ACO savings rates, BPCI episode costs, and MIPS quality signal medians. Example: MSSP Track 1 ACOs generating median 2.3% savings above benc |
get_travel_nurse_rate_benchmark | Use when benchmarking travel nurse contract rates or negotiating with a staffing agency. Returns bill-rate medians and bands by specialty and state. Example: ICU travel nurse median bill rate $95/hr in Illinois, p75 $108/hr — agencies billing above $115/hr are 21% above market — renegotiation typica |
get_ehr_cost_per_bed | Use when benchmarking EHR maintenance costs before a contract renewal or evaluating health IT budget efficiency. Returns benchmark cost per licensed bed with optional gap analysis when actual cost and bed count are provided. Example: Epic maintenance median $4,500/bed — 300-bed hospital at $6,200/be |
get_healthcare_vendor_market_rate | Use when benchmarking a healthcare vendor quote or preparing a supply chain contract negotiation. Returns market rates for EHR, staffing, food service, waste management, and med-surg by facility type. Example: Healthcare food service median $18.40/patient day for acute care — facilities above $22/pa |
get_staffing_agency_markup_analysis | Use when evaluating staffing agency pricing or negotiating a travel nurse or locum contract. Returns median markup percentage with low/high band by agency and specialty type. Example: AMN Healthcare median markup 40%, Cross Country 37%, Aya 38% — ICU and OR specialties carry 5-8% premium — agencies |
get_gpo_contract_benchmark | Use when benchmarking GPO contract performance or building a supply chain cost reduction case for a hospital board. Returns typical GPO savings percentage, leakage rate, and top savings categories. Example: Acute care GPO median savings 18% vs non-contract pricing — leakage rate 22% means 1-in-5 pur |
get_physician_group_benchmark | Use when evaluating physician employment agreements, benchmarking compensation for recruitment, or preparing a medical staff compensation report. Returns median total compensation by specialty and state from BLS OES 2024 data. Example: Illinois cardiologist median $461K total compensation — interven |
get_hospital_supply_chain_benchmark | Use when benchmarking hospital supply chain efficiency against CMS peer cohort or building a materials management cost reduction case. Returns supply cost as percentage of operating expense at p25/p50/p75 by bed size and state. Example: 200-bed community hospital — supply cost 19.4% of operating exp |
get_asc_benchmark | Use when benchmarking ASC financial performance, evaluating an ASC acquisition, or preparing an administrator board report. Returns cost per case medians and revenue mix percentages by specialty. Example: Orthopedic ASC cost per case median $4,200 — facilities above $5,100 are in the bottom cost qua |
get_healthcare_category_intelligence | Use when researching which vendors dominate AI recommendations in a healthcare technology category or validating a health IT vendor selection. Returns top recommended vendors, AI consensus narrative, and sample size from healthcare-specific citation analysis. Example: EHR category — Epic leads at 67 |
get_market_intelligence_brief | Use when producing a quick industry intelligence brief or validating market narrative for a strategy deck. Returns AI-generated market summary, up to six key themes, and sentiment skew for any industry. Example: Healthcare IT market — POSITIVE sentiment 68%, key themes: EHR consolidation, AI-assiste |
get_industry_spend_benchmark | Use when validating total IT spend against industry peers or building a software budget baseline for a CFO board presentation. Returns median monthly total software stack spend, category breakdown, and productivity tool medians by industry. Example: Mid-market healthcare org — median total SaaS spen |
get_category_disruption_signal | Use when assessing whether a software category faces near-term displacement risk, or timing a market entry or exit decision. Returns disruption risk score from 0 to 1 with evidence strings from citation volume patterns. Example: ERP category — disruption risk score 0.71, evidence: 34 citations refer |
get_competitive_displacement_signal | Use when tracking competitive threats to an incumbent vendor or identifying switching trends in a software category. Returns vendors mentioned as replacements for a target vendor with switch narrative and mention counts. Example: Salesforce displacement — HubSpot replacing in SMB at 28 mentions, Dyn |
get_vendor_risk_signal | Use when screening a vendor for financial instability or procurement risk before a long-term contract commitment. Returns a risk score from 0 to 1 with risk indicators and negative mention evidence. Example: Vendor X scores 0.72 risk — indicators: customer churn citations, pricing disputes, product |
get_market_structure_signal | Use when assessing software category maturity, timing a market entry, or evaluating consolidation risk in a category. Returns market structure signal (consolidating or fragmenting) with citation evidence. Example: HR tech category — CONSOLIDATING signal, top 3 vendors hold 71% of AI citation share — |
get_macro_market_signal | Use when a current macro environment snapshot is needed for a trading brief, CFO board presentation, or investment committee context. Returns Fed funds rate, Treasury yields, CPI, PCE, and employment data when FRED API is configured. Example: Fed funds 5.33%, 10Y 4.42%, CPI 3.1% — rates and inflatio |
get_sector_ai_intelligence | Use when producing equity research, tracking brand share in AI sector coverage, or benchmarking a company AI visibility against sector peers. Returns top brands by AI mention share, sector trend narrative, and themed bullets for any equity sector. Example: Financials sector — JPMorgan leads at 34% c |
get_fomc_rate_probability | Use when providing monetary policy narrative context for a macro brief, investment committee, or CFO rate planning session. Returns illustrative cut, hike, and hold probabilities for the next three FOMC meetings based on current FRED fed funds data. Scenario planning tool — not futures-implied marke |
get_elliott_waves | Use when a technical trader needs wave counts, targets, and invalidation levels for major assets. Returns wave position, degree, target high/low, invalidation, and confidence for BTC, SPY, TLT, Gold. Example: wave label, target band, invalidation, and confidence score per asset. $0.50 USDC per call. |
get_macro_playbook | Use when a trader or portfolio manager needs current regime label and tactical positioning. Returns active regime, verifiable FOMC facts, live market snapshot, model interpretation, concurrent playbooks, and key levels. Example: regime label with playbook actions and risk triggers. $0.50 USDC per ca |
get_trader_signals | Use when a macro agent needs a full live signal stack in one call. Returns Fed funds, 2s10s, VIX, BTC, WTI, silver, gold, DXY, SOFR, MOVE, verifiable FOMC facts, model interpretation, and cross-asset sentiment. Example: live rates, vol, and commodities with FOMC facts separated from forward-looking |
get_pe_portfolio_benchmark | Use when benchmarking portco technology spend for PE operating partners or building a software cost reduction case across a portfolio. Returns median software spend per company, category breakdown, and savings opportunity percentage. Example: Mid-market portco median $480K/yr — 18% savings opportuni |
get_saas_market_intelligence | Use when assessing a SaaS category investment thesis, competitive dynamics, or market momentum before a strategic decision. Returns growth signal, AI citation leaders, and disruption risk for any software category. Example: CRM category — GROWING signal, Salesforce leads at 42% citation share, HubSp |
get_investment_category_signal | Use when evaluating VC software category attractiveness or assessing portfolio category exposure before an investment decision. Returns growth signal, top brands, and citation evidence for any software category. Example: AI infrastructure category — GROWTH signal, top brands Nvidia 67% citation shar |
get_portfolio_vendor_intelligence | Use when conducting vendor diligence for a PE or VC portfolio company before a value creation initiative. Returns market rate data, brand index snapshot, and competitive displacement signals for any vendor. Example: Portco using Salesforce at $12,400/mo — market median $8,400/mo, 48% above market — |
get_vendor_benchmark | Use when a CFO or procurement lead needs org-specific vendor pricing vs market before renewal or negotiation. Returns market_low, market_median, market_high, position_label, negotiation tactics, estimated_savings_monthly from benchmark_cache when fresh, or guidance to load intelligence in Stratalize |
get_company_salary_disclosure | Use when benchmarking compensation against disclosed employer wages or assessing H-1B wage practices before a talent acquisition or competitive hire. Returns DOL LCA and H-1B wage aggregates by employer, job title, state, and fiscal year. Example: Microsoft H-1B software engineer — prevailing wage L |
get_employer_h1b_wages | Use when analyzing an employer H-1B compensation strategy or benchmarking tech sector wages against DOL prevailing wage data. Returns prevailing wage statistics, certified job titles, wage levels, and state distribution from DOL LCA filings. Example: Google H-1B — software engineer Level IV prevaili |
get_hospital_care_compare_quality | Use when evaluating hospital quality for a referral network decision, acquisition target assessment, or competitive quality analysis. Returns CMS Hospital Compare scores — safety, readmissions, patient experience, mortality, and overall star rating by hospital. Example: Northwestern Memorial — 5-sta |
get_federal_contract_intelligence | Use when researching a company federal revenue concentration, identifying government contract competitors, or assessing vendor dependency on federal business. Returns contract obligation data by vendor, agency, NAICS code, and fiscal year from USASpending. Example: Acme IT Services — $847M federal o |
get_intel_owner_profile | Use when assessing a construction owner's claims history before bidding a contract or negotiating a change order. Returns aggregate finding counts by defect family and outcome, decisions in the corpus, and days and dollars claimed versus awarded. Example: USACE Norfolk District, 42 findings, 31% den |
get_intel_contractor_profile | Use when vetting a contractor or bidder before a teaming decision or subcontract award. Returns the entity record plus award and bid participation history by role (winner, bidder, or vehicle holder). Example: Acme Paving LLC, winner on 14 of 61 bids (23% win rate), low bidder on 9 of those 14: a thi |
get_intel_lettings_search | Use when scoping upcoming or recent construction lettings in a target geography before allocating bid and estimating resources. Returns bid tabulation line items filtered by owner, county, district, state, and letting date range. Example: Cook County, IL lettings in the last 90 days: 23 lettings, 34 |
get_intel_unit_prices | Use when benchmarking a bid line-item price against recent public lettings before finalizing an estimate. Returns minimum, maximum, average, and sample count unit prices for a pay item code, filterable by owner, state, and county. Example: pay item 20101100 (clearing and grubbing) in Texas, average |
get_intel_findings_search | Use when researching tribunal precedent for a specific defect or claim type before filing or defending a construction claim. Returns findings filtered by defect family, claim type, outcome, owner, and keyword, with docket number and case name from the underlying decision. Example: differing-site-con |
get_intel_join | Use when researching a contractor's track record with a specific owner before a bid or teaming decision. Returns awards where that contractor (by UEI) participated under that owner plus the owner's general tribunal-decision findings for context. Example: USACE Norfolk District and a mid-Atlantic mar |
get_bank_financial_intelligence | Use when evaluating a bank for acquisition, partnership, correspondent banking, or competitive analysis in a local market. Returns FDIC-sourced assets, deposits, capital ratios, loan quality, and peer benchmark positioning. Example: Midwest Community Bank — $2.4B assets, CET1 12.3% (well above 6% mi |
get_workplace_safety_benchmark | OSHA injury and illness rate benchmarks by company, industry, NAICS code, and state. Industry composite benchmarks available immediately with no sync required — establishment-specific data enabled when OSHA sync is connected. Covers injury rates, top-quartile performance, and EMR context for insuran |
get_cfpb_complaint_intelligence | Use when assessing consumer finance risk, benchmarking complaint volume against peers, or conducting pre-acquisition due diligence on a financial institution. Returns CFPB complaint rollups by company and product — volume, issue themes, and response rate trends. Example: Regional Bank X — 847 CFPB c |
get_provider_market_intelligence | Use when assessing physician supply in a market, evaluating a healthcare network expansion, or benchmarking provider density for population health strategy. Returns NPI registry physician counts and market structure by specialty and state. Example: Illinois cardiology — 847 cardiologists, 2.3 per 10 |
get_public_company_financials | Use when pulling public company financials for a comparable company analysis, M&A due diligence, or investor brief. Returns SEC EDGAR financial statement data — income statement, balance sheet, and key ratios from filed reports. Note: cache may reflect prior quarter — verify against latest SEC filin |
get_cms_open_payments_profile | Use when assessing physician payment transparency risk, evaluating manufacturer relationships, or preparing Sunshine Act compliance reporting. Returns CMS Open Payments aggregates by physician or manufacturer — payment amounts, types, and program year breakdown. Example: Dr. Smith — $847K general pa |
get_uspto_patent_intelligence | Use when assessing a company IP portfolio strength, tracking competitor patent activity, or preparing M&A patent due diligence. Returns USPTO filing rollups by assignee — patent counts, filing years, and CPC classification. Example: Qualcomm — 47,000+ active patents, 3,200 filed in 2023, concentrate |
get_github_ecosystem_intelligence | Use when assessing a technology vendor open-source presence, evaluating developer community strength, or researching a company GitHub footprint before a technical due diligence. Returns organization profile and top repository stats — stars, forks, contributors, and language breakdown. Example: Hashi |
get_stealth_tokenize_entities | Anonymize free-text PII and named entities with deterministic typed tokens in one paid call, fail-closed by design and cryptographically attested for verification. Uses a per-request ephemeral secret, so consistency is guaranteed only within the call; cross-session consistency and org dictionary mat |
get_form_d_new_raises | Use when tracking new private placement activity via SEC Form D filings in a recent window. Returns Form D filings from EDGAR full-text search with optional state and SIC filters. Source: SEC EDGAR EFTS. $0.10 USDC per call. |
get_8k_material_events | Use when monitoring material issuer events via recent 8-K filings for a ticker. Returns 8-K filing metadata from EDGAR submissions with optional item-code filter hints. Source: SEC EDGAR submissions. $0.10 USDC per call. |
get_form4_insider_cluster | Use when detecting insider trading clusters from Form 4 filing density over a window. Returns form4_filing_count, cluster_score, and activity signal for a ticker. Source: SEC EDGAR Form 4 cluster analysis. $0.50 USDC per call. |
get_13f_holdings_delta | Use when comparing institutional 13F-HR filing quarters for QoQ holdings change context. Returns current and prior quarter filing pairs with delta summary scaffolding. Source: SEC EDGAR 13F submissions. Requires ticker or cik. $0.50 USDC per call. |
get_new_litigation_alerts | Use when monitoring new federal dockets filed against a party in the last N days. Returns docket alerts from CourtListener; zero results is a legitimate empty answer. Source: CourtListener docket search. $0.10 USDC per call. |
get_litigation_risk_composite | Use when synthesizing litigation risk from party profile, docket intelligence, and optional judge analytics. Composite degrades transparently when partial CourtListener sources fail. Source: CourtListener composite. $0.50 USDC per call. |
get_regulatory_comment_deadlines | Use when tracking Federal Register proposed rules and notices with open comment periods. Filters comment windows client-side on comments_close_on when API cannot server-side filter. Source: Federal Register API. $0.10 USDC per call. |
get_verify_receipt_batch | Use when an auditor or compliance agent needs programmatic batch verification of governed settlement receipts. Accepts receipt IDs or pasted receipt JSON; returns per-item three-layer trust verdicts (post-quantum signature, digest binding, on-chain anchor) with zero persistence. Read and verify only |
get_data_freshness_attestation | Use when an examiner or compliance workflow needs a post-quantum signed attestation of screening-list currency. Returns list_version and as-of metadata for synced OFAC, OIG LEIE, or SAM exclusion datasets — the same versions bound into screening responses. Input dataset: ofac, oig, or sam. $1.00 USD |
get_x402_traffic_diligence | Use when you need attested know-your-agent diligence on inbound x402 traffic to Stratalize. Reports settlement count, tool-call concentration, cadence, traffic classification, and sweep-bot heuristics for wallets that have paid Stratalize — plus optional CDP Bazaar listing metadata for a target reso |
get_x402_seller_statement | Use when an x402 seller or marketplace operator needs an attested on-chain settlement statement for a payee wallet over a bounded period. Ingests Base mainnet USDC Transfer logs, classifies likely x402 settlements, assembles STMT-JCS-1 aggregates and methodology, ML-DSA-65 signs, persists, and ancho |
get_vendor_onboarding_dossier | Use when onboarding a vendor or counterparty and you need one signed composite dossier for examiner-facing diligence. Fans in OFAC, OIG LEIE, and SAM exclusion screening (each with list_version), NPI provider verification, vendor market rate, and contract intelligence — degrading per-section when a |
get_bank_counterparty_diligence | Use when diligencing a bank or financial institution counterparty before onboarding, funding, or transaction approval. Fans in bank regulatory benchmark, AML regulatory benchmark, OCC enforcement actions, credit union peer benchmark, and CFPB complaint intelligence — degrading per-section on source_ |
get_cre_acquisition_diligence | Use when underwriting a CRE acquisition and need one signed composite across cap rates, CRE debt, operating costs, property tax, debt-stress, and location climate risk score. Degrades per-section on source_unavailable. Inputs location and state (required); optional asset_class, property_type, market |
get_ai_regulatory_landscape | Use when standing up or auditing an AI governance program and need one signed snapshot across NIST AI RMF, EU AI Act, US state AI legislation, Colorado AI Act, model risk management standards, and UK FCA PS7/24 coverage. All inputs optional — returns full framework composite; optional nist_function, |
get_financial_deal_readiness | Use when assessing financial health and deal-readiness for M&A, lending, or investment committee review. Fans in earnings quality, working capital, WACC, corporate debt, credit spread, and ESG benchmarks — degrading per-section on source_unavailable. Input sector (required); optional industry, credi |
get_healthcare_vendor_gpo_diligence | Use when diligencing a healthcare vendor or GPO relationship. Fans in healthcare vendor market rate, GPO contract benchmark, FDA recall history, payer intelligence, and hospital supply chain benchmark — degrading per-section on source_unavailable. Inputs vendor_name and bed_size (required). $3.00 US |
get_litigation_enforcement_snapshot | Use when assessing litigation and enforcement exposure for a counterparty. Fans in litigation risk composite, new litigation alerts, federal court cases, FTC enforcement history, and OCC enforcement actions — degrading per-section (including CourtListener-dependent alerts) on source_unavailable. Inp |