RateAPI — live US mortgage, auto, HELOC, personal & deposit rates

Add recipients (email + optional name) to a campaign. Up to 50 per request, 200 per campaign. Duplicate addresses are ignored.

Compare projected cost of renting vs buying a home over a holding period, anchored to LIVE market mortgage rates. Given home price, down payment, monthly rent, and a holding period, returns year-by-year cumulative cost of each path (rent vs PITI), equity built, net cost of owning after sale, and the breakeven year where buying becomes cheaper than renting. If no rate is supplied, the current best market rate for the state is used. Use for 'should I rent or buy?' questions.

Frame a buy/refi-now vs wait recommendation. Combines recent rate movement (direction + magnitude over 1w/2w/4w) with break-even sensitivity on the borrower's loan to return a forward 'lock now' vs 'wait' lean, the bps swing that would change the call, and the cost of waiting. Use for 'should I lock now or wait for rates to drop?' questions. Distinct from get_rate_delta (raw historical deltas only) — this adds a forward recommendation. Not a rate forecast.

Lock-window-aware lock-vs-float-down recommendation for a deal already in the pipeline. Given a known lock-expiration date, the currently locked rate, and the float-down cost, returns a defensible hold-lock vs exercise-float-down call a loan officer can document — combining recent market movement (1w/2w/4w) with payment and break-even math on this loan. Builds on the same recent-movement signal as assess_buy_timing but framed around the lock window/expiration. Not a rate forecast.

Score an array of inline financing scenarios in one stateless call; returns ranked decisions and top offers per item — no persisted cohorts, no per-borrower HTTP loops.

Build a year-by-year amortization / payoff schedule for a loan: total lifetime interest, principal/interest split per period, and a what-if extra-payment accelerator showing months saved and interest saved. Resolves the market rate from real credit-union offers when no rate is provided.

Run compliance/suitability guardrails over a financing scenario and an optional recommendation. Returns flags (red/yellow with code + message) for things like DTI strain, long auto terms with negative-equity risk, possible balloon payments, and stale market data, plus generic disclaimers and an overall verdict (ok/caution/stop). Use this before presenting a rate recommendation to a borrower.

LENDER-side 'is my offer competitive' check — input your OWN published rate for a state+product, get the market percentile, bps vs the state median, and a leading/competitive/overpriced verdict. This is for a loan officer or credit union benchmarking their published pricing against the live market distribution. Do NOT use this for a consumer's quote: if the user is a BORROWER asking whether a rate they were offered is fair, use rate_sanity_check instead.

`relative_memberships` carries confirmed current/deceased relative membership scoped to one exact target credit union; one institution is never reused for another. Check whether a user can JOIN specific credit unions (field-of-membership eligibility). Batch-friendly: pass 1-50 credit_union_ids (from get_financing_decision offers, list_credit_unions, or get_credit_union) plus whatever is known about the user (home, worksite, and payroll geography are independent facts; employer, occupation, military_status, school plus school_relationship, and worship are also supported). City facts require their same-role state or a recognized same-role ZIP that uniquely identifies one state, and are accepted only when the closed Census gazetteer resolves them. Returns one row for every requested credit union. Positive outcomes include open_to_anyone, likely_eligible, eligible_via_employer, and eligible_via_military. A school name alone is not a positive signal: school_relationship is required to affirm a typed student, alumni, or school-employee path. Only a graph carrying exact active-publication lineage governs the top compatibility verdict; a publication-less shadow graph remains diagnostic and cannot replace the flat result. A non-match is returned as unknown, with `unknown_reason: fom_completeness_unaffirmed` when the published field-of-membership corpus is not attested complete. The legacy `geo_mismatch` enum value is reserved for wire compatibility and is not emitted by this MCP boundary without a future typed closed-world attestation. Verdicts are guidance based on each credit union's published membership criteria; the final membership determination is always the institution's. Non-matches carry `missing_facts` for the named institutions: the exact question to ask next, the `fact_field` an answer populates, and the institution's own words. A check that returns unknown for all of them and a question for each is a SUCCESSFUL call, not a failure — ask the questions, merge the answers into the same request, and call again. Home geography accepts both the original `zip`/`state`/`county` names and the `home_zip`/`home_state`/`home_county` aliases emitted by `missing_facts`; do not send conflicting values in both forms. Fact fields, in full — supply every one you know: `home_zip`, `home_state`, `home_county`, `home_city`; `work_zip`, `work_state`, `work_county`, `work_city`; `payroll_zip`, `payroll_state`, `payroll_county`, `payroll_city` (payroll can differ from the worksite and is a separate door); `property_zip`, `property_state`, `property_county`, `property_city` (where they OWN property — never inferred from where they live, and an absentee owner qualifies); `facility_zip`, `facility_state`, `facility_county`, `facility_city` (where their business maintains a location); `occupation`; `employer`; `school` plus `school_relationship` (student/alumni/employee — a school name without a relationship affirms nothing); `military_status` plus `military_service_state` (state National Guard doors need the state); `worship`; `family_relation` plus `relative_employers`, `relative_schools`, `relative_associations` (a great many people qualify only through a relative — ask); `applicant_kind` (person/trust/organization/partnership/corporation — some charters admit entities, and a person is never rejected by an entity-only door, only left unknown); and `asserted_org_qualifiers` (narrowings the person asserts about themselves, e.g. "assigned as a recruiter in Arkansas").

Compare baseline and candidate confirmed person facts across the same 1-19 explicit products. Both catalogs use one pinned immutable eligibility graph snapshot; rate rows retain independent evidence and as_of. Returns access, membership-path, and like-for-like published-price basis-point deltas: APY for deposits, APR for lending when both sides publish APR, otherwise nominal rate only when both sides publish nominal rate. It never mixes APR and nominal rate. Never describe missing access as denial or infer savings, underwriting, approval, or final terms.

Compare the best real rates across MULTIPLE lending products in a single call — e.g. show a buyer mortgage vs HELOC, or new vs used auto. Runs the decision engine for each product and returns a ranked, true-cost (APR + fees) table. Use this instead of calling get_financing_decision repeatedly. Each product returns its top offer with rate, APR, and monthly payment.

Compare one baseline person-fact panel with one candidate panel against the same active eligibility snapshot and exact product request. Use this for explicit what-if questions such as adding a confirmed employer or association. Newly reachable means current positive evidence now proves a path; no_longer_reachable or absence never proves ineligibility. Supply only facts the person confirmed, preferably canonical *_org_ids from resolve_eligibility_entities. Person facts are forwarded transiently and are not stored by this tool.

Apples-to-apples multi-lender ranking by TOTAL cost of a loan (upfront origination/lender fees + lifetime interest over the holding period), not just the headline rate. Re-ranks real credit union offers and flags when the lowest-rate lender is not the cheapest overall.

Subscribe a monitor to a SPECIFIC named credit union's published rate and alert via webhook when that CU changes its rate (vs the aggregate market-best decision). Returns the monitor with a webhook_signing_secret (shown once) and a baseline snapshot of the CU's current rate.

Create a branded rate-email campaign: on a cadence, email the campaign's recipient list the latest rates for one or more states (or a named region preset) under the org's branding, with ONE OR MORE products (1-5, no duplicates). Each product is one of: {category:'mortgage', subtype:'30-year-fixed'|'15-year-fixed'}, {category:'auto', condition:'new'|'used'|'any', term_months?:36|48|60|72|84} (auto = cars only), or {category:'rv'|'boat'|'motorcycle', condition:'new'|'used'|'any'}. Defaults to a single 30-year-fixed mortgage if products is omitted. Created 'paused'; add recipients, then activate via update_email_campaign (activation requires branding display_name + business_address). Requires a Pro plan. Provide exactly one of state_code, state_codes, or region.

Create a new decision monitor that watches for rate changes and sends webhook notifications when conditions are met. Returns the monitor with a webhook_signing_secret for verifying webhook payloads.

Permanently delete a saved cohort by id. This action cannot be undone.

Delete a scheduled digest by id. Stops the recurring email.

Delete a branded rate-email campaign and its recipients. This cannot be undone.

Permanently delete a monitor. This action cannot be undone.

Delete a saved scenario by id.

Send a test webhook for a monitor using a simulated rate change. This actually delivers an HTTP request to the monitor's configured webhook URL. IMPORTANT: a test delivery is NOT signed with the monitor's signing secret — only a hash of that secret is stored, so test deliveries use a placeholder and will FAIL signature verification. Use this to test payload handling, not signature verification. Only use when the user explicitly requests a test webhook delivery.

Borrower-facing home affordability estimate: given gross income, existing monthly debts, down payment, and front-end/back-end DTI caps, compute the max monthly payment, max loan amount, and max home price. Surfaces the max_loan annuity engine. If no rate is supplied, the current best market rate for the state is used.

Total monthly housing cost (PITI): principal+interest plus property tax, homeowners insurance, PMI, and HOA, so affordability reflects real monthly outlay. If no rate is supplied, the current best market rate for the state is used.

Evaluate a caller-supplied panel of 1-10 named fact profiles for one exact product against one serving snapshot, deduplicating reachable institutions and exact offers. This is descriptive only for the supplied panel: never call it a population estimate, conversion rate, approval forecast, or negative eligibility result. Use neutral profile labels instead of names, emails, account numbers, or other direct identifiers. Profiles are forwarded transiently and are not stored by this tool; unknown remains unknown.

Explain WHY each top lender ranked where it did for a financing decision. Takes a full decision scenario (same shape as get_financing_decision) and returns a structured per-offer cost breakdown (rate, points, fees, lifetime interest), scoring signals, how much each offer beats the next by, and a plain-language summary of the ranking weights. Use this when a user asks why one lender beat another.

Turn a person's own words about themselves into the structured facts the eligibility tools accept. Pass their sentence verbatim ("I'm a nurse at a Tulsa hospital, I live in Broken Arrow, my late father was a TTCU member") and this returns each fact it could read, with the exact words it read it from, a confidence, and a needs_confirmation flag. THIS DOES NOT DECIDE ELIGIBILITY and never returns a credit union: it only fills in fields. Show the extracted facts to the user and get confirmation on every fact with needs_confirmation=true (family relationships, relatives' employers and associations, applicant kind, and asserted qualifiers are always flagged, because a wrong reading of those changes the answer). Then pass `person_search_body` — plus whatever the user confirmed — to find_eligible_credit_unions, which is what actually decides. If extraction is unavailable you get facts: [] and no eligibility signal at all; ask the user for fields directly instead. `confidence` is the extraction model's own uncalibrated self-report and gates only autofill — quote `evidence.quote` to the user, not the number. This call costs 3 API units.

Use when someone asks for "credit unions near me," the closest credit union, local credit-union branches, or nearby alternatives to a bank. Given a 5-digit ZIP, returns credit unions ordered by the estimated straight-line distance to each institution's closest NCUA-reported branch. Includes approximate miles, branch address, and profile identifiers for checking rates, services, and membership. Distances use ZIP centers and are not driving distance.

`relative_memberships` carries confirmed current/deceased relative membership scoped to one exact target credit union; one institution is never reused for another. `next_questions.unlocks_cu_count` counts membership decisions an answer may clarify, never guaranteed products. Discovery tool: find candidate credit unions a person may be able to JOIN, from their own facts rather than from a list of institutions. Pass any combination of home, worksite, or payroll geography (these are independent), occupation, employer, school (+school_relationship), associations, military_status, and worship; at least one discriminating fact is required, or pass willing_to_join_association=true as the sole discriminator to search documented joinable-association paths. City facts require their same-role state or a recognized same-role ZIP that uniquely identifies one state, and are accepted only when the closed Census gazetteer resolves them. This evaluates a bounded, prioritized candidate set, not the entire credit-union fleet: read `candidate_limit`, `candidate_set_truncated`, and `candidate_sources`, and never interpret an absent institution as unavailable or ineligible. Returns four buckets within that candidate set — eligible (a verified path already applies), conditionally_eligible (one more step, e.g. joining an association, with the cost and join URL when known), possibly_eligible (a path may apply but a requirement could not be confirmed), and unknown (we could not decide — either we hold no rules for the institution or the supplied facts cannot decide the rules we hold). Every non-positive entry carries a machine-readable `unknown_reason`: `geo_inputs_missing` / `org_inputs_missing` / `inputs_missing` mean ONE MORE FACT FROM THE USER would resolve it, so ask for it and call again; `no_rules` means we hold nothing for that institution and asking will not help; `incomplete_fom`, `fom_completeness_unaffirmed`, `low_confidence_rules` and `unmodeled_condition` mean we hold rules but will not turn a failure against them into a no. Each entry also carries `coverage` — {state, rules_held, last_confirmed_at, fom_affirmed} — describing what we HOLD about the institution as opposed to what we concluded about the person. Each entry carries the credit union id, name, state, confidence, and deterministic reasons. Use this to find supported candidates; use check_membership_eligibility when you already have specific credit_union_ids. Credit unions are never listed as ineligible — absence of evidence is never treated as evidence of absence, and the final membership determination is always the institution's. Every non-positive entry now also carries `missing_facts`: the exact question to ask the person next, the `fact_field` their answer populates, why it matters, and the institution's own words. The response's top-level `next_questions` ranks those questions across all institutions by how many they unlock — ASK THE TOP ONE TO THREE, MERGE THE ANSWERS INTO THE SAME REQUEST BODY, AND CALL AGAIN. Two or three turns is the intended shape of this tool; a single call is a first draft. Stop when `next_questions` is empty, when the top entry's `unlocks_cu_count` is below 2, or after three turns. `unanswerable` lists what no question can fix — institutions we hold no rules for, boundaries we can state but not decide (census tracts, school districts, a radius around an office the page never identifies), and rule sets whose completeness nobody affirmed; do not ask the user about those. Fact fields, in full — supply every one you know: `home_zip`, `home_state`, `home_county`, `home_city`; `work_zip`, `work_state`, `work_county`, `work_city`; `payroll_zip`, `payroll_state`, `payroll_county`, `payroll_city` (payroll can differ from the worksite and is a separate door); `property_zip`, `property_state`, `property_county`, `property_city` (where they OWN property — never inferred from where they live, and an absentee owner qualifies); `facility_zip`, `facility_state`, `facility_county`, `facility_city` (where their business maintains a location); `occupation`; `employer`; `school` plus `school_relationship` (student/alumni/employee — a school name without a relationship affirms nothing); `associations`; `military_status` plus `military_service_state` (state National Guard doors need the state); `worship`; `family_relation` plus `relative_employers`, `relative_schools`, `relative_associations` (a great many people qualify only through a relative — ask); `willing_to_join_association`; `applicant_kind` (person/trust/organization/partnership/corporation — some charters admit entities, and a person is never rejected by an entity-only door, only left unknown); and `asserted_org_qualifiers` (narrowings the person asserts about themselves, e.g. "assigned as a recruiter in Arkansas").

Use when someone asks for the best mortgage, auto-loan, HELOC, personal-loan, student-loan, equipment-loan, or credit-card rates near them and provides a ZIP. Finds the nearest NCUA-reported branch set, keeps credit unions with a current product-matched published rate, and ranks those offers by lowest APR with approximate distance as a tie-breaker. HELOC matching excludes closed-end home-equity loans. This is a local shopping shortlist: distance is straight-line, membership is not guaranteed, and published APR is not personalized approval.

Find the best fresh, evidence-backed credit-union rates reachable from this person’s membership facts. This composed graph-first operation evaluates the complete active US credit-union fleet BEFORE rates are queried, so a strong out-of-state employer, association, school, military, family, property, work/payroll, or facility door is not lost behind a candidate cap or state-only rate search. `reachable_now` requires a verified membership path, satisfied supplied product dimensions, and fresh evidenced published pricing; `reachable_after_action` requires the same product proof plus a documented membership action. Unknown or mismatched term, intent, vehicle condition, or occupancy remains `unresolved`, never silently matched. `no_published_offer` means no matching fresh evidenced rate was found. Deposits rank published APY only. Lending ranks published APR rows first and separately labeled nominal-rate rows second, never comparing APR and rate as one measure. Every price includes verbatim evidence and as_of, and routed membership results preserve graph/publication lineage and source proof. Use product-aware questions only as bounded facts that may clarify. Published pricing is not approval or guaranteed final availability.

Produce a clean, client-facing markdown rate comparison report a loan officer can share with a buyer. Pass either a saved scenario_id, or an inline client_name + comparison result (from get_financing_decision/compare_products).

Turn a saved client scenario into a public, branded, shareable URL (https://app.rateapi.dev/r/TOKEN) that anyone can view without logging in. Returns a token and url. The link shows the client name, scenario inputs, and the ranked comparison with a "Powered by RateAPI" footer. Use revoke_share to disable a link later.

Get rate benchmark statistics (min/median/max APR) across all institutions. Use this for market analysis, comparing user quotes against market rates, or building benchmark dashboards. Returns statistics for mortgages (30yr fixed, 15yr fixed, and `mortgage_arm` — one bucket covering every adjustable-rate mortgage regardless of initial fixed period), auto loans (new/used — cars only), RV/boat/motorcycle/powersports (first-class vehicle categories), HELOCs, and personal loans. Each product shows the lowest APR institution, median APR, and count of institutions.

Get a single saved cohort by id, including all members and the last scan snapshot (triage list).

Introspect what mortgage/loan data the API covers BEFORE scanning — which states, lenders, and product types are present, row counts per segment, and last-updated freshness per segment. Returns a coverage matrix so an agent can pick a scannable state/product before calling scan_savings or get_financing_decision. Mirrors the /meta global counts, expanded into a per-segment matrix. Boats, RVs, motorcycles, and powersports are first-class product categories; auto means cars.

Reference tool: Get a credit union's rates, membership eligibility, and source-labelled NCUA quarterly profile: members, assets, year opened, charter, reported services, and branch locations. Eligibility annotates published criteria and never asserts that an individual is ineligible; profile facts are regulatory snapshots, not live prices. Use this when a user asks about a specific credit union. For personalized rate recommendations, use get_financing_decision instead.

Best/median/spread credit-union deposit APY by product, term, and state, with per-CU peer ranking. Pass the MCP field `product` using one exact underscore value: savings, cd, share_certificate, money_market, ira_cd, ira, or share_savings. The MCP server translates it to REST `product_category`; do not send `product_category`, `mma`, or `money-market` to this tool. Deposits quote APY (no APR); CDs/share certificates include term. Current + recent data; history is retention-bounded.

Deposit beta (repricing sensitivity) = change in deposit APY per 100bps change in a benchmark/market rate — the core credit-union/bank ALM & interest-rate-risk (IRR) model input. Pass the MCP field `product` using an exact underscore value such as `money_market`; do not send `product_category`, `mma`, or `money-market`. Derived from RateAPI's retained published deposit-rate history. SHORT-WINDOW / retention-bounded: full-cycle beta needs multi-year history (roadmap) — results ship with an explicit confidence/depth caveat. Deposits quote APY, never APR. Aggregate published rates only — never member/borrower data.

DOCS: return the full text of one RateAPI documentation page by slug (from search_docs) or by its published URL. Documentation only — it describes the contract, not live rates. Available slugs: quickstart, authentication, rate-limits-and-pricing, coverage, freshness, evidence-and-methodology, quoting-rules, eligibility, endpoints, mcp-server, products-and-parameters, errors-and-troubleshooting, deprecation-policy.

Read the bounded, cursor-paginated feed of currently active eligibility publication replacements since an ISO timestamp. Use it to invalidate caches keyed by credit_union_id or publication identity. It exposes aggregate publication metadata only: no personal facts, no historical verdict, and no claim that a person is eligible or ineligible.

Enterprise RateAPI Routes coverage: how many US credit unions RateAPI holds live, verbatim-evidenced membership rules for (and what share of the active fleet that is), how the rules split by kind, how many counties, states and employers they name, verification status, and freshness. The `authority` object distinguishes exact immutable active publications from older graph and flat compatibility records; `evidence_sources` reports the public source mix. Returns a dated `headline` sentence that can be quoted verbatim. Use this BEFORE find_eligible_credit_unions or check_membership_eligibility when the user asks how complete, authoritative, or fresh the eligibility data is. Aggregate only — no institution-level rows; those come from the eligibility tools. Never reports credit data: the rule schema has no condition kind for credit score, income or debt. An institution absent from the graph is undecided, never ineligible.

Get the organization's current email branding (display name, logo URL, brand color, intro, business address, reply-to).

Get data extraction statistics showing the scale and health of rate data collection. Use this to understand extraction volumes, product coverage, and data freshness. Supports filtering by date range and product type. Great for building transparency dashboards or monitoring data collection health.

RECOMMENDED WHEN SHOPPING: Get personalized financing recommendations for ANY loan or credit product across every major type: mortgages (30yr/15yr/20yr/10yr fixed and ARMs), auto loans (new/used/CPO, 36-84 month terms), RV/boat/motorcycle/powersports loans, HELOCs (fixed/variable), personal loans (secured/unsecured), student loans, equipment loans, and credit cards (rewards, cash_back, secured, balance_transfer, low_rate, business, platinum, student). Analyzes current market offers and returns actionable recommendations with explanations. Use this instead of looking up raw rates when the user is asking "what rate can I get?" and does NOT yet have an offer. IMPORTANT: if the user ALREADY has a quoted rate and is asking whether it is good/fair/competitive ("I was quoted 6.9%, is that any good?"), call rate_sanity_check instead — it returns a percentile verdict on their specific number, which is what that question is actually asking. Provide the user's state, intent (purchase/refinance/cash_out/balance_transfer/new_credit), and amount for personalized advice.

Loan-officer competitive-landscape report: ranked roster of the top N lenders publishing a given mortgage product in a state today — per-lender rows (name, best APR/rate, product, position, bps above the leader) — plus the market min/median/max. The market median is INSTITUTION-level — one vote per lender, using each lender's best APR (basis = total_lenders, not market.count) — so a lender publishing a large rate matrix cannot pull it. Extends get_benchmarks (which returns only min/median/max + the single lowest institution) with the full ranked table.

Get detailed information about a specific monitor by its ID.

Get rollup stats for the account's rate monitors: total, active, and webhooks sent. Complements list_monitors.

Evaluate one person across 1-19 explicit loan or deposit selectors using one exhaustive eligibility snapshot. Returns separate membership, published availability, product suitability, published pricing, underwriting, and approval layers. Lead only with reachable_now or reachable_after_action; unresolved and no_published_price are unknown, never a denial. Published APY, APR, or clearly labeled nominal rate is not a personalized quote, underwriting result, preapproval, commitment, or guarantee. Every returned published price carries source evidence and as_of.

Get non-personal, evidence-bound membership-access metadata for up to 50 exact deposit product references. Returns active-publication path kinds and documented joinable-association actions alongside the current evidenced product rate. This does NOT decide whether a person is eligible, easy to qualify, approved, or within a published balance/audience constraint; unavailable evidence stays unavailable.