MCP Tool Catalog — analyze_deal, best_use, solve_max_offer, comps & more

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analyze_deal FREE

The core tool: a full underwrite of one property under one strategy. Returns the 0–100 deal score, the strategy's headline metrics (the same ones the REIzer analyzer screens show), stress-test scenarios with verdicts, break-even thresholds, and a shareable 30-day report_url.

Argument		Description
`strategy`	required	One of `ltr`, `str`, `brrr`, `multifamily`, `flip`, `newc`.
`inputs`	required	Deal inputs in camelCase engine keys. Minimum: `price` plus the income driver (see the strategy table below). Rates and percents are fractions — `0.0675`, never `6.75`. Omitted operating inputs get documented defaults, and the response lists them under `assumptions.estimated_fields`.

example — call

analyze_deal({
  "strategy": "ltr",
  "inputs": { "price": 285000, "marketRent": 3100,
              "downPct": 0.25, "rate": 0.0675, "term": 30,
              "closing": 6000, "vacancyPct": 0.05,
              "taxes": 3200, "insurance": 1500,
              "mgmtPct": 0.08, "maintPct": 0.05, "capexPct": 0.05 }
})

example — response (abbreviated)

{
  "score": 96, "verdict": "Strong",
  "metrics": { "monthly_cash_flow": 636.85, "dscr": 1.4594,
               "cap_rate": 0.0852, "cash_on_cash": 0.0989, … },
  "stress": [ 7 scenarios, each with a verdict ],
  "thresholds": { "break_even_rent": 2282.47, "max_rate": 0.0878, … },
  "summary": "Strong (96/100). $637/mo cash flow, DSCR 1.46, …",
  "report_url": "https://reizer.io/report.html?id=…"
}

best_use FREE

One property, every angle. Send a superset of inputs; REIzer runs every strategy the property qualifies for and ranks them by score. Strategies missing their required inputs are listed under skipped with the reason.

Argument		Description
`inputs`	required	One property's inputs across strategies — e.g. `price`, `marketRent`, `adr` + `occupancy`, `rehabBudget`, `arv`, `units`.

example — response (real ranking)

"best_use": "ltr"
"ranked":  1. ltr   91  Strong
         2. str   77  Strong
         3. brrr  29  Weak
         4. flip   5  Weak
"skipped": multifamily, newc  (missing unit / land inputs)

solve_max_offer FREE

Works backwards: instead of "is this price good?", it answers "what's the most I can pay?" — a binary search over the real engine, not a rule-of-thumb formula. Each strategy has sensible default targets; override any of them.

Argument		Description
`strategy`	required	Strategy to solve under.
`inputs`	required	Deal inputs. `price` is optional — the asking price or ARV anchors the price-derived defaults.
`targets`	optional	Target overrides, e.g. `{"monthlyCF": 400, "cocReturn": 0.08}`. Rentals default to cash-on-cash ≥ 8%, DSCR ≥ 1.2, cash flow ≥ $0; flips to after-tax margin ≥ 10% and annualized ROI ≥ 15%; BRRRR adds capital recovery ≥ 80%.

example — response (real solve)

// same inputs as above, with targets { monthlyCF: 400, cocReturn: 0.08 }
"mao": 303657
"binding_constraint": { "label": "cash-on-cash return", "target": 0.08 }
"metrics_at_mao": { "monthlyCF": 546.10, "dscr": 1.3697, "cocReturn": 0.08 }
"ceilings_per_target": { "cocReturn": 303657, "dscr": 346599, "monthlyCF": 333691 }

list_strategies FREE

Machine-readable discovery: every strategy with its required and optional inputs and their meanings. AI clients call this first when unsure what a strategy needs — no arguments.

pull_comps API KEY

Real comparables from licensed data — the same feed as the in-app comps panel. Returns comparable sales (with a value estimate and range), rental comps (with a rent estimate), and ZIP-level market stats. Counts against the account's monthly property-comp allowance.

Argument		Description
`street`	required	Street address incl. house number, e.g. "812 7th St SE".
`city`	required	City name.
`state`	required	Two-letter state, e.g. "TX".
`zip`	optional	ZIP code — disambiguates the address when a street name repeats in a metro.
`saleCount`	optional	Comparable sales to return (default 10).
`rentCount`	optional	Rental comps to return (default 10).

response shape

{
  "sales":   { "value", "valueRange": {low, high}, "medianPrice", "medianPpsf",
              "rows": [ {address, beds, baths, sqft, yearBuilt, price,
                        pricePerSqft, saleDate, distanceMi, …} ] },
  "rentals": { "rent", "rentRange", "medianRent", "rows": [ … ] },
  "market":  { "zip", "saleMedianPrice", "saleMedianDom", "saleYoyChange",
              "rentMedianPrice", "rentYoyChange", "saleHistory", … }
}

str_market_data API KEY

Short-term-rental market performance for a location: nearby STR listings with ADR, occupancy, and revenue quartiles. Needs coordinates — your AI geocodes the address first. Counts against the monthly STR-comp allowance.

Argument		Description
`latitude`	required	Subject latitude.
`longitude`	required	Subject longitude.
`bedrooms`	optional	Bedrooms filter (default 2).
`baths`	optional	Bathrooms filter.
`guests`	optional	Guest-capacity filter.

Strategy input cheat-sheet

What analyze_deal minimally needs per strategy (everything else defaults, labeled in the response):

Strategy	Required inputs	Analyzes
`ltr`	price, marketRent	Long-term rental: cash flow, DSCR, cap rate, 10-yr projection
`str`	price, adr, occupancy	Short-term rental: revenue, break-even occupancy, levers
`brrr`	price, rehabBudget, marketRent, arv	BRRRR: refi scenarios, capital recovery, post-refi cash flow
`multifamily`	price, units	Rent-roll driven: NOI, value-add lift, per-unit economics
`flip`	price, rehabBudget, arv	Fix-n-flip: after-tax profit, 70% rule, break-even sale
`newc`	landPrice, livingSqft, buildPsf, btsArv	New construction: build-to-sell vs build-to-rent head-to-head

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