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

Financial benchmarks: yield curve, FX, WACC, M&A multiples, PE returns, and bank capital ratios.

- Trust score: 71/100 (medium)
- Change this week: +9
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `www.stratalize.com`: 71/100 (this document), [markdown](https://verifymcp.io/servers/com-stratalize-finance/api-mcp-public.md), [page](https://verifymcp.io/servers/com-stratalize-finance/api-mcp-public)

## Channel facts

- Endpoint: `https://www.stratalize.com/api/mcp-public?vertical=finance`
- 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**: 63/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 5273 tokens (~114/item across 46 items; 46 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**: 69/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 7% 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-finance https://www.stratalize.com/api/mcp-public?vertical=finance
```

### Codex

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

### opencode

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

### OpenClaw

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

### Hermes

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

### Other

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

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 71, +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 70, +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 69, +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 64, +1)

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

### 2026-07-28 (score 63, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 62, +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 61)

First indexed and scored.

## MCP tools (46)

### `get_fomc_rate_probability` (~111 tokens)

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 market odds. Example: Hold probability 68% at next meeting, cut probability 31% — conditioned on fed funds at 5.33% and latest CPI print. Source: FRED St. Louis Fed.

### `get_elliott_waves` (~91 tokens)

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.

Input parameters:

- `asset` (string): Asset symbol or "all" (default all)

### `get_macro_playbook` (~63 tokens)

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.

### `get_trader_signals` (~99 tokens)

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 interpretation. Source: FRED/EIA.

### `get_bank_financial_intelligence` (~138 tokens)

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% minimum), NPL ratio 0.42% vs 0.71% peer median — strong capital position, favorable acquisition target profile. Source: FDIC BankFind synced call report data.

Input parameters:

- `bank_name` (string, required): e.g. JPMorgan, Wells Fargo, First National Bank

### `get_cfpb_complaint_intelligence` (~125 tokens)

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 complaints in 2023, 34% on mortgage servicing, complaint volume 2.3x peer median — elevated consumer protection risk signal. Source: CFPB Consumer Complaint Database synced data.

Input parameters:

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

### `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_imf_weo_macro_snapshot` (~114 tokens)

Use when providing global macro context for an international expansion brief, country risk assessment, or board-level economic outlook presentation. Returns IMF WEO macro composites — GDP growth, inflation, and current account balance by country group. Example: Emerging market composite — GDP growth 4.2% vs advanced economy 1.7%, inflation diverging at 7.8% — growth premium exists but requires currency and political risk premium in discount rate. Source: IMF WEO static composite, semi-annual update.

### `get_eia_energy_public_snapshot` (~105 tokens)

Use when current energy price data is needed for a commodity brief, input cost analysis, or energy sector context in a CFO or investment brief. Returns WTI crude and natural gas spot prices when EIA API is configured. Example: WTI crude $78.40/bbl, natural gas $2.31/MMBtu — energy input costs 12% below year-ago levels, favorable for manufacturing and transportation operating margins. Source: US Energy Information Administration.

### `get_working_capital_benchmark` (~93 tokens)

Use when benchmarking working capital efficiency or preparing a CFO cash management brief. Working capital benchmarks — DSO, DPO, DIO, and cash conversion cycle (CCC) by industry and company size. Source: Hackett Group annual survey and BLS composite. CFO and treasury benchmark for lender covenant prep and cash flow optimization.

Input parameters:

- `company_size` (string)
- `industry` (string, required)

### `get_wacc_benchmark` (~95 tokens)

Use when valuing a business, setting hurdle rates, or benchmarking discount rates for M&A analysis or capital allocation. WACC benchmarks by sector and market cap tier from Damodaran annual dataset — used for DCF valuation, M&A pricing, board approval, and capital allocation. The most cited public finance benchmark. Updated January annually.

Input parameters:

- `market_cap_tier` (string)
- `sector` (string, required)

### `get_public_market_multiples` (~109 tokens)

Use when building a public comps table, benchmarking a private company valuation, or preparing a fundraising benchmark. Public market valuation multiples — EV/EBITDA, EV/Revenue, P/E, and P/S by sector with p25/p50/p75 bands. Source: Damodaran January 2024 dataset. Used for board prep, M&A pricing, fundraising benchmarks, and DCF sanity checks. Free.

Input parameters:

- `context` (string)
- `sector` (string, required)

### `get_ma_multiples_benchmark` (~105 tokens)

Use when valuing an acquisition target, benchmarking deal pricing, or preparing a fairness opinion. M&A transaction multiples — acquisition EV/EBITDA, EV/Revenue, and control premiums by industry and deal size. Source: Damodaran transaction dataset and public deal aggregates. Used by corp dev, PE deal teams, M&A advisors, and CFOs preparing fairness opinions.

Input parameters:

- `deal_size_tier` (string)
- `industry` (string, required)

### `get_corporate_debt_benchmark` (~113 tokens)

Use when assessing a company debt capacity, benchmarking leverage against sector peers, or preparing a refinancing or credit rating discussion. Corporate leverage and debt benchmarks — Net Debt/EBITDA, interest coverage, and debt maturity profiles by credit rating tier and industry. Source: S&P Capital IQ public aggregates and Damodaran. Used by CFOs and treasurers for refinancing, covenant setting, and credit rating management.

Input parameters:

- `credit_rating_tier` (string)
- `industry` (string, required)

### `get_audit_fee_benchmark` (~126 tokens)

Use when benchmarking audit costs, evaluating auditor proposals, or preparing an audit committee RFP. Audit fee benchmarks — total fees and fees as a percentage of revenue by company revenue band and auditor tier (Big 4 vs national vs regional). Source: Audit Analytics public aggregate data. Used by CFOs and audit committees in auditor RFPs and fee negotiations.

Input parameters:

- `annual_revenue_usd` (number, required): Annual revenue in USD, e.g. 50000000 for $50M
- `auditor_tier` (string)
- `industry` (string)

### `get_pe_return_benchmark` (~99 tokens)

Use when benchmarking fund performance, setting LP return expectations, or evaluating a GP track record. Private equity and venture return benchmarks — IRR, TVPI, DPI by vintage year and strategy (buyout, growth equity, venture). Source: Cambridge Associates public benchmark summaries. Used by PE GPs, LPs, and fund CFOs for performance reporting and fundraising.

Input parameters:

- `strategy` (string, required)
- `vintage_year` (number)

### `get_venture_benchmark` (~77 tokens)

Venture capital round benchmarks — pre-money valuation, round size, dilution, and option pool standards by stage and sector. Source: Carta State of Private Markets quarterly. Used by founders, VC CFOs, and early-stage investors for round pricing and cap table modeling.

Input parameters:

- `sector` (string)
- `stage` (string, required)

### `get_bank_regulatory_benchmark` (~88 tokens)

Bank regulatory capital and financial performance benchmarks — CET1, Tier 1 leverage, NIM, efficiency ratio, charge-off rates, and loan-to-deposit ratio by asset size tier. Source: FDIC call report public aggregates. For bank CFOs, risk officers, and bank analysts.

Input parameters:

- `asset_size_tier` (string, required)
- `bank_type` (string)

### `get_insurance_benchmark` (~73 tokens)

Insurance financial performance benchmarks — combined ratio, loss ratio, expense ratio, and reserve adequacy by line of business. Source: NAIC annual statistical report. For insurance CFOs, actuaries, and analysts reviewing underwriting performance.

Input parameters:

- `company_size` (string)
- `line_of_business` (string, required)

### `get_credit_union_benchmark` (~79 tokens)

Credit union financial performance benchmarks — capital ratios, net interest margin, loan growth, and delinquency rates by asset size. Source: NCUA quarterly call report public data. For credit union CFOs preparing for NCUA exams and board reporting.

Input parameters:

- `asset_size_tier` (string, required)
- `charter_type` (string)

### `get_fx_rate_benchmark` (~144 tokens)

Live major currency pair benchmarks — USD/EUR, USD/JPY, USD/GBP, USD/CNY, USD/CAD, USD/MXN, DXY broad TWI, carry trade spread, and weekly/monthly/YTD rate change. Source: FRED. Updated daily. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Input parameters:

- `base_currency` (string)

### `get_credit_spread_benchmark` (~140 tokens)

Live investment grade and high yield credit spread benchmarks from FRED ICE BofA indices — OAS by rating tier, TED spread, 2s10s Treasury spread, and distress signal. Updates daily. For credit analysts and fixed income PMs. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Input parameters:

- `rating_tier` (string)

### `get_commodity_benchmark` (~131 tokens)

Live commodity price benchmarks — WTI crude, natural gas, gold, copper, wheat, soybeans. Weekly and monthly price changes, inflation pressure signal. Source: FRED. Updated daily. For traders and macro analysts. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Input parameters:

- `category` (string)

### `get_yield_curve_benchmark` (~138 tokens)

Live US Treasury yield curve — 1M through 30Y yields with daily and weekly basis point changes, 2s10s and 2s30s spreads, inversion signal, SOFR, and curve shape classification. Source: FRED. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Input parameters:

- `tenor` (string)

### `get_earnings_quality_benchmark` (~87 tokens)

Earnings quality and financial statement risk benchmarks — accruals ratio, cash conversion, and revenue recognition risk by sector. Source: SEC EDGAR aggregate + Sloan accruals model (academic standard). For CFOs, auditors, and analysts assessing financial reporting risk before M&A or investment.

Input parameters:

- `revenue_recognition_model` (string)
- `sector` (string, required)

### `get_labor_market_benchmark` (~136 tokens)

Live labor market benchmarks from FRED — unemployment, U-6 underemployment, JOLTS job openings, quit rate, labor participation, weekly claims, wage growth. Tight/balanced/loosening signal for macro agents and portfolio managers. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Input parameters:

- `focus` (string)

### `get_inflation_benchmark` (~141 tokens)

Live inflation benchmarks from FRED — CPI, core CPI, PCE, core PCE, 5Y and 10Y TIPS breakeven expectations, shelter and medical care components. Fed target gap, anchoring signal, and policy implication for macro agents. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Input parameters:

- `measure` (string)

### `get_consumer_sentiment_benchmark` (~129 tokens)

Live consumer sentiment benchmarks from FRED — University of Michigan sentiment, Conference Board confidence, retail sales, PCE, personal saving rate. Strong/moderate/weak consumer signal for GDP and equity agents. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Input parameters:

- `focus` (string)

### `get_global_equity_benchmark` (~150 tokens)

Global equity index benchmarks — S&P 500, Nasdaq, Russell 2000, Stoxx 600, DAX, FTSE 100, Nikkei 225, Hang Seng, Shanghai Composite, MSCI EM. YTD returns, P/E ratios, and risk-on/risk-off global signal. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Input parameters:

- `region` (string)

### `get_esg_benchmark` (~77 tokens)

ESG benchmarks by sector — carbon intensity Scope 1/2, net zero commitments, SBTi alignment, board independence, pay equity, and ESG composite scores. Sources: EPA GHGRP, MSCI ESG methodology. For sustainability agents and ESG analysts.

Input parameters:

- `focus` (string)
- `sector` (string)

### `get_climate_risk_benchmark` (~83 tokens)

Climate financial risk benchmarks — physical risk (flood, hurricane, wildfire, heat), transition risk (carbon pricing scenarios, stranded assets), and lender implications. Source: FEMA NFIP, NGFS scenarios. For ESG and risk agents.

Input parameters:

- `property_type` (string)
- `region` (string)
- `risk_type` (string)

### `get_aml_regulatory_benchmark` (~72 tokens)

AML regulatory benchmarks — FinCEN SAR filing rates, OFAC SDN counts and recent additions, BSA enforcement fine history, travel rule thresholds, and compliance staffing benchmarks. For compliance agents and financial institution risk officers.

Input parameters:

- `focus` (string)
- `institution_type` (string)

### `get_ncua_credit_union_financials` (~179 tokens)

Use when evaluating a credit union for partnership, acquisition, membership, or competitive benchmarking in a local market. Returns NCUA call report financials — assets, deposits, loans, net worth ratio, delinquency rate, and ROA — with peer comparison signals. The same financial data NCUA examiners review during examination preparation. Well-capitalized threshold is 7% net worth ratio — institutions below this face mandatory corrective action. Example: ABC Federal Credit Union — $2.1B assets, 11.2% net worth ratio (59% above minimum), 0.38% delinquency vs 0.71% peer average — financially strong, low credit quality risk. Source: NCUA Call Report Data.

Input parameters:

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

### `get_sec_insider_trading` (~79 tokens)

SEC Form 4 insider transaction history — executive buy/sell filings in the last 90 days with filing dates and links. Returns insider activity signal. Source: SEC EDGAR. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `ticker` (string, required)

### `get_sec_beneficial_ownership` (~86 tokens)

Schedule 13D/13G beneficial ownership filings — identifies activist (13D) or passive (13G) 5%+ shareholders with intent classification. Returns activist signal. Source: SEC EDGAR. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `ticker` (string, required)

### `get_bls_sector_employment` (~157 tokens)

Use when benchmarking workforce planning against sector labor market conditions, assessing industry growth trajectory for strategic planning, providing economic context for board reporting, or evaluating talent acquisition timing for a specific industry. Returns BLS payroll employment by major sector with month-over-month change, year-over-year change, and trend classification from the official establishment survey covering 650,000 US worksites — the same data the Federal Reserve uses to assess labor market conditions. Example: Healthcare sector — 8.41M employed, +47K MoM, +3.2% YoY, EXPANDING for 14 consecutive months — persistent hiring demand supports above-market compensation benchmarks. Source: Bureau of Labor Statistics Current Employment Statistics.

Input parameters:

- `sector` (string, required)

### `get_job_openings_intelligence` (~93 tokens)

JOLTS labor market intelligence from BLS: job openings, quits rate, layoffs rate, and tight/loose/normal interpretation. Use for workforce planning, wage pressure forecasting, and recession early-warning agents. Source: BLS JOLTS. $0.10 standard. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

### `get_employment_cost_index` (~83 tokens)

BLS Employment Cost Index year-over-year change for total compensation, wages, and benefits. Use when modeling labor cost inflation, contract escalation, and margin pressure in operating plans. Source: BLS ECI. $0.10 standard. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

### `get_producer_price_by_industry` (~102 tokens)

BLS Producer Price Index by industry with index level and year-over-year change. Covers software, healthcare services, banking, construction, retail, hospital, and consulting. Use for input cost benchmarking and PPI pass-through analysis. Source: BLS PPI. $0.10 standard. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `industry` (string, required)

### `get_agricultural_commodity_benchmark` (~105 tokens)

Spot agricultural commodity price from FRED IMF primary commodity series for soybeans, wheat, corn, cotton, or coffee. Returns USD price, unit, and observation period for crop hedging, food cost modeling, and trade exposure agents. Source: FRED / IMF. $0.02 atomic. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

Input parameters:

- `commodity` (string, required)

### `get_shipping_cost_benchmark` (~91 tokens)

Baltic Dry Index shipping cost benchmark from FRED with trend classification (elevated, depressed, normal) and five-year average. Use when assessing global trade volume, freight inflation, or supply chain cost pressure. Source: FRED / Baltic Exchange. $0.02 atomic. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

### `get_retail_sales_benchmark` (~86 tokens)

US advance retail sales from FRED in billions USD with month-over-month and year-over-year percent change. Use for consumer demand monitoring, recession signals, and revenue forecasting agents. Source: FRED / US Census Bureau. $0.02 atomic. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

### `get_personal_savings_benchmark` (~85 tokens)

BEA personal saving rate from FRED with long-run average comparison and above-average flag. Use when assessing household balance sheet health, consumption durability, and macro recession risk. Source: FRED / BEA. $0.02 atomic. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

### `get_copper_price_benchmark` (~83 tokens)

IMF Grade A copper price in USD per metric ton with year-over-year change and industrial demand significance note. Use as a coincident indicator for global manufacturing and construction cycles. Source: FRED / IMF. $0.02 atomic. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.

### `get_bls_inflation_components` (~144 tokens)

Use when analyzing inflation exposure by spending category, structuring or reviewing vendor contract escalation clauses, benchmarking healthcare or real estate cost inflation, or providing monetary policy context for a CFO or treasury brief. Medical care CPI and housing CPI consistently diverge from headline inflation — critical for healthcare budget planning and commercial lease negotiations. Example: Medical care CPI +3.8% YoY vs headline CPI +3.1% — healthcare costs inflating 23% faster than the general economy, directly driving hospital operating budget overruns in fixed-price service contracts. Source: Bureau of Labor Statistics CPI — the Federal Reserve's primary inflation benchmark.

Input parameters:

- `category` (string)

### `get_world_bank_country_indicators` (~213 tokens)

Use when assessing country risk for international expansion, evaluating a foreign market for investment or partnership, benchmarking a country's economic trajectory for capital allocation decisions, or producing ESG country-level scoring. Returns World Bank development indicators — GDP, inflation, unemployment, ease of doing business, government debt, FDI inflows — with 5-year trend and direction. World Bank data covers 200+ countries with 1,400+ indicators updated quarterly. Example: Brazil — GDP growth 2.9% (2023), inflation declining from 9.3% to 4.6%, ease of doing business ranked 124th globally, net FDI inflows $65.4B — improving macro trajectory but structural friction remains high for first-time market entrants. Source: World Bank Open Data.

Input parameters:

- `country_code` (string, required): ISO 3166-1 alpha-2 or alpha-3 country code (e.g. BR, DEU, JP, US, GB)
- `indicator` (string, required)

## Diagnostics

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

## Score history

- 2026-08-03: 71
- 2026-08-02: 70
- 2026-08-01: 70
- 2026-07-31: 69
- 2026-07-30: 64
- 2026-07-29: 63
- 2026-07-28: 63
- 2026-07-27: 62
- 2026-07-26: 61

## Links

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