# Stratalize Healthcare (remote · www.stratalize.com)

CMS benchmarks, travel nurse rates, pharmacy spend, billing risk, and payer intelligence.

- Trust score: 70/100 (medium)
- Change this week: +9
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `www.stratalize.com`: 70/100 (this document), [markdown](https://verifymcp.io/servers/com-stratalize-healthcare/api-mcp-public.md), [page](https://verifymcp.io/servers/com-stratalize-healthcare/api-mcp-public)

## Channel facts

- Endpoint: `https://www.stratalize.com/api/mcp-public?vertical=healthcare`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.1.1`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 80/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 59/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 3893 tokens (~134/item across 29 items; 29 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 68/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 5% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http com-stratalize-healthcare https://www.stratalize.com/api/mcp-public?vertical=healthcare
```

### Codex

```toml
[mcp_servers.com-stratalize-healthcare]
url = "https://www.stratalize.com/api/mcp-public?vertical=healthcare"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-stratalize-healthcare": {
      "type": "remote",
      "url": "https://www.stratalize.com/api/mcp-public?vertical=healthcare",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add com-stratalize-healthcare --url https://www.stratalize.com/api/mcp-public?vertical=healthcare --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  com-stratalize-healthcare:
    url: "https://www.stratalize.com/api/mcp-public?vertical=healthcare"
```

### Other

```json
{
  "mcpServers": {
    "com-stratalize-healthcare": {
      "type": "http",
      "url": "https://www.stratalize.com/api/mcp-public?vertical=healthcare"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-03 (score 70, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-01 (score 69, +1)

No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 68, +5)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 63, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-29 (score 62, +1)

No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-28 (score 61, 0)

- [security] Tool “get_drug_recall_status” rewrote its description, which is the text the model reads

### 2026-07-27 (score 61, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 60)

First indexed and scored.

## MCP tools (29)

### `get_cms_facility_benchmark` (~123 tokens)

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 hospital type. Example: 300-bed acute care hospital in Illinois — peer group and percentile outputs show where operating metrics sit versus cohort benchmarks. Source: CMS HCRIS cost reports.

Input parameters:

- `bed_size` (number, required)
- `hospital_type` (string)
- `state` (string, required)

### `get_payer_intelligence` (~123 tokens)

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 7.1% — prior auth burden 34% higher for specialist services — top quartile denial rate is 5.1%. Source: Stratalize national revenue cycle composite.

Input parameters:

- `payer_name` (string)
- `specialty` (string)

### `get_cms_star_rating` (~115 tokens)

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 require 18-month mortality improvement program — 3-star hospitals represent 41% of the national distribution. Source: CMS Care Compare methodology.

Input parameters:

- `current_star_rating` (number)
- `hospital_name` (string)
- `state` (string)

### `get_pharmacy_spend_benchmark` (~168 tokens)

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 hospital — drug cost $287/adjusted patient day vs $241 peer median — 340B eligibility could recover $1.8M annually — specialty drugs driving 61% of cost variance. Source: Stratalize static model derived from published 340B savings ranges.

Input parameters:

- `annual_patient_days` (number)
- `annual_pharmacy_spend` (number)
- `bed_size` (number)
- `enrolled_340b` (boolean)
- `state` (string)

### `get_nadac_drug_benchmark` (~192 tokens)

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_detected when CMS republishes the same effective date. Example: NDC 42385096230 — NADAC $1.45422/EA as_of 2026-07-15 effective 2026-06-17. Source: CMS NADAC (data.medicaid.gov DKAN, weekly). | x402 SLA: $0.02 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_sources[] discloses provenance string bound by synthesis.output_hash.

Input parameters:

- `ndc_or_name` (string, required)

### `get_cost_plus_price` (~174 tokens)

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, and canonical purchase URL — never labeled as a benchmark. Example: NDC 42385096230 — unit price $0.963 transparent retail price estimate (cost+15% model). Source: Cost Plus Drugs public API. | x402 SLA: $0.02 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_sources[] discloses estimate provenance bound by synthesis.output_hash.

Input parameters:

- `ndc_or_name` (string, required)
- `quantity_units` (number)

### `get_drug_recall_status` (~164 tokens)

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 product's recalls. Example: NDC 41163-703-10 — Class II nasal spray recall records with termination dates. Source: openFDA drug/ndc and drug/enforcement. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_sources[] discloses provenance bound by synthesis.output_hash.

Input parameters:

- `ndc_or_name` (string, required)

### `get_billing_coding_risk` (~156 tokens)

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 vs 48% national benchmark — flagged HIGH upcoding risk — OIG cardiology audit focus active in 2024-2025 cycle. Source: CMS and OIG compliance composite.

Input parameters:

- `annual_claim_volume` (number)
- `level_4_5_percentage` (number): Percentage of E/M claims at level 4 or 5
- `specialty` (string)

### `get_value_based_care_performance` (~154 tokens)

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 benchmark — top quartile at 4.8% — organizations below 1.5% savings face program exit risk. Source: CMS VBC program data composite.

Input parameters:

- `bed_size` (number)
- `current_vbc_revenue_pct` (number): Percentage of revenue from value-based contracts
- `program_type` (string)
- `specialty` (string)

### `get_travel_nurse_rate_benchmark` (~120 tokens)

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 typically recovers $180K-$240K annually per 10 FTE travelers. Source: BLS and Stratalize SIA-style composite.

Input parameters:

- `specialty` (string, required)
- `state` (string, required)

### `get_ehr_cost_per_bed` (~135 tokens)

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/bed is 38% above market — renegotiation trigger especially strong at 5+ year renewal cycles. Source: KLAS 2024, Kaufman Hall EHR TCO composite.

Input parameters:

- `annual_cost` (number)
- `bed_count` (number)
- `vendor_name` (string, required)

### `get_healthcare_vendor_market_rate` (~120 tokens)

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/patient day are 20% above market — GPO competitive rebid typically recovers 8-12%. Source: CMS and Stratalize healthcare vendor composite.

Input parameters:

- `category` (string)
- `vendor_name` (string, required)

### `get_staffing_agency_markup_analysis` (~119 tokens)

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 billing above 45% markup are 12-18% above market. Source: Stratalize SIA 2024-style composite.

Input parameters:

- `agency_name` (string)
- `specialty` (string)

### `get_gpo_contract_benchmark` (~107 tokens)

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 purchases bypass contract — leakage above 30% triggers mandatory compliance programs at most health systems. Source: HFMA and CMS composite.

Input parameters:

- `category` (string)

### `get_physician_group_benchmark` (~109 tokens)

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 — interventional cardiology 34% above general cardiology — organizations below 25th percentile face retention risk in competitive markets. Source: BLS Occupational Employment Statistics.

Input parameters:

- `specialty` (string, required)
- `state` (string)

### `get_hospital_supply_chain_benchmark` (~125 tokens)

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 expense vs 16.8% peer median — closing the gap to median recovers $2.6M annually at $130M operating budget. Source: CMS HCRIS cost reports.

Input parameters:

- `bed_size` (number, required)
- `state` (string)

### `get_asc_benchmark` (~113 tokens)

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 quartile — orthopedic mix at 60% of cases maximizes margin vs ophthalmology-heavy mix. Source: ASCA and CMS 2024 composite.

Input parameters:

- `specialty` (string)
- `state` (string)

### `get_healthcare_category_intelligence` (~111 tokens)

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% AI citation share, Oracle Health 18%, MEDITECH 9% — consensus near-universal for large health systems, fragmenting below 200 beds. Source: Stratalize AI citation composite.

Input parameters:

- `category` (string, required)

### `get_hospital_care_compare_quality` (~111 tokens)

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-star overall, top decile on mortality and safety, HCAHPS 87th percentile — benchmark for quality-driven referral network design. Source: CMS Care Compare synced data.

Input parameters:

- `hospital_name` (string, required): Hospital or facility name

### `get_provider_market_intelligence` (~118 tokens)

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 10,000 population vs 2.7 national median — below-median supply signals referral network expansion opportunity. Source: CMS NPI Registry synced data.

Input parameters:

- `city` (string)
- `specialty` (string, required)
- `state` (string, required)

### `get_cms_open_payments_profile` (~126 tokens)

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 payments from 3 manufacturers in 2022, 67% from one device company in consulting fees — concentration above $100K triggers enhanced compliance review. Source: CMS Open Payments Sunshine Act database.

Input parameters:

- `manufacturer_name` (string)
- `program_year` (number)
- `recipient_name` (string, required)

### `get_stratalize_overview` (~112 tokens)

START HERE — Returns the complete Stratalize tool catalog: governed MCP tools across finance, healthcare, governance, real estate, crypto, and intelligence. Available via public MCP (no auth) or x402 micropayments on Base ($0.02 atomic · $0.10 benchmark · $0.50 synthesis · $1.00 premium · $3.00 outcome pack). Org intelligence, agent governance, and role briefs require OAuth. Call this first to discover tools by role or vertical.

### `get_npi_provider_verification` (~106 tokens)

Use when verifying a clinician or organization NPI against CMS NPPES before contracting or credentialing. Returns enumeration status, taxonomy, license state, and identity fields from live NPPES lookup. Source: CMS NPPES Registry. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `npi` (string)
- `provider_name` (string)
- `state` (string)

### `get_openfda_adverse_events` (~91 tokens)

FDA FAERS adverse event signal for a drug — total reports, serious events, deaths, hospitalizations, top reactions with percentages, and signal level (HIGH / ELEVATED / MONITOR / LOW). Source: OpenFDA. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `drug_name` (string, required)

### `get_irs_990_intelligence` (~97 tokens)

IRS Form 990 nonprofit financial data — total revenue, expenses, net assets, program expense ratio, executive compensation, revenue trend, and financial health signal. Source: ProPublica Nonprofit Explorer. Essential for evaluating nonprofit health systems, universities, and foundations. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `org_name` (string, required)

### `get_fda_recall_history` (~154 tokens)

Use when evaluating a pharmaceutical company, medical device manufacturer, or healthcare vendor for product safety risk, supply chain exposure, or regulatory compliance standing. Returns FDA recall classifications (Class I = risk of serious harm, Class II = moderate risk, Class III = unlikely to cause harm) with product descriptions and recall reasons. Class I recalls trigger mandatory FDA press releases and procurement review obligations. Example: MedSupply Corp — 2 Class I drug recalls in 36 months: contaminated IV solutions (2022) and mislabeled injectable (2023) — pattern of serious quality control failures requiring immediate vendor review. Source: OpenFDA Enforcement Reports.

Input parameters:

- `company_name` (string, required)
- `product_type` (string)

### `get_drug_adverse_events` (~108 tokens)

FAERS drug adverse event reports from OpenFDA by medicinal product name. Returns serious event counts, reactions, outcomes, and recent report chronology. Use for pharmacovigilance monitoring, safety signal detection, and clinical risk agents. Source: FDA FAERS. $0.10 standard. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `drug_name` (string, required)
- `limit` (integer)

### `get_device_clearances` (~99 tokens)

FDA 510(k) device clearance history from OpenFDA by device name. Returns K numbers, applicants, decisions, and receipt dates. Use for medtech competitive intelligence, regulatory pathway research, and supplier qualification. Source: FDA 510(k) database. $0.10 standard. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `device_name` (string, required)

### `get_drug_label_intelligence` (~99 tokens)

FDA drug label intelligence from OpenFDA DailyMed extracts. Returns brand and generic names, manufacturer, route, indications summary, and warnings summary. Use for formulary review, pharmacology research, and adverse event context. Source: FDA drug labels. $0.10 standard. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `drug_name` (string, required)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/com-stratalize-healthcare/api-mcp-public#diagnostics

## Score history

- 2026-08-03: 70
- 2026-08-02: 69
- 2026-08-01: 69
- 2026-07-31: 68
- 2026-07-30: 63
- 2026-07-29: 62
- 2026-07-28: 61
- 2026-07-27: 61
- 2026-07-26: 60

## Links

- Remote endpoint: https://www.stratalize.com/api/mcp-public?vertical=healthcare
- Repository: https://github.com/Stratalize/Stratalize
- Website: https://www.stratalize.com/
- Changelog RSS feed: https://verifymcp.io/servers/com-stratalize-healthcare/api-mcp-public/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/com-stratalize-healthcare/api-mcp-public/changelog.json
- HTML version of this page: https://verifymcp.io/servers/com-stratalize-healthcare/api-mcp-public