financeratecalc

endpoint

https://frc-mcp.ziyetis.workers.dev

door code

ea7f92c7dbebaeb2

protocol

streamable-http ·2025-06-18

authentication

none observed

public key

none — nobody has proven they own this listing · is it yours? claim it

karma

0 · newcomer

Is financeratecalc live?

Yes — it answered the hub's last check (checked 51m ago). It answered 99% of checks over the last 30 days.

Is financeratecalc free to use?

Yes — the hub reached it with no key and no payment.

What tools does financeratecalc have?

17 tools: get_lender_denial_stats, get_metro_lender_gap, check_claim_contract, run_cohort, get_state_denial_stats, get_application_outcomes, resolve_fha_annual_mip, get_door_effect_summary, ….

Is financeratecalc safe to connect?

The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

• get_application_outcomes open 17h ago

  ANSWERS: "how many FHA applications are withdrawn", "what share of FHA applications never reach a decision", "how many approved FHA loans are not taken", "why is the denied share 16.8% here and the denial rate 22.1% there", "where do <lender>'s FHA applications end". Returns the five HMDA ends of an application the lender acted on — originated, approved but not accepted, denied, withdrawn, closed for incompleteness — as shares of applications acted on (actions 1-5), plus the approved-not-accepted share of approvals, nationally or for one of the 100 largest FHA lenders, each with its receipt. The denied share here is on a larger base than the published denial rate (22.1% of decisioned applications); both are returned so they can be reconciled. NOT FOR: why an application ended where it did (process, market, applicant pool and reporting practice are not separable in the record), lender quality, or any individual outcome. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "lender": {
        "type": "string",
        "description": "Optional: lender name, slug or LEI (top-100 set). Omit for the national figures."
      }
    }
  }

  arguments 9 lines copy
• resolve_fha_annual_mip open 17h ago

  ANSWERS: "what is the FHA annual MIP for a $300,000 loan at 85% LTV over 15 years", "what MIP rate applies to my FHA case". PARAMS: base_loan_amount (USD), ltv_pct (e.g. 96.5), term_years, case_number_date (YYYY-MM-DD). Resolves the exact cell of HUD Mortgagee Letter 2023-05 and returns the annual rate in basis points, the upfront rate, the matched cell, the rule id with effective date and sha256, and a sentence you may quote. If a parameter is missing it returns block with CONDITION_MISSING and no number: the table has eleven cells and a guess is wrong more often than right. NOT FOR: case numbers before 2023-03-20, HECM/reverse or Title I loans, or any monthly payment figure.

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  {
    "type": "object",
    "properties": {
      "ltv_pct": {
        "type": "number",
        "description": "Loan-to-value in percent, e.g. 96.5"
      },
      "term_years": {
        "type": "number",
        "description": "Loan term in years"
      },
      "base_loan_amount": {
        "type": "number",
        "description": "Base loan amount in USD, before upfront MIP is financed"
      },
      "case_number_date": {
        "type": "string",
        "description": "FHA case number assignment date, YYYY-MM-DD"
      }
    }
  }

  arguments 21 lines copy
• get_door_effect_summary reads open 10h ago

  ANSWERS: "does it matter which lender you apply to", "how much of a denial is the lender rather than the borrower", "what is the Door Effect". Returns the variance decomposition: lender identity is associated with about 38 percent of the explainable variation in FHA denial outcomes across 859,090 decisions (McFadden 0.1712 to 0.2760), with model, sample and limits. Association on observable federal-record characteristics, not causation; HMDA carries no credit scores. NOT FOR: saying a lender caused a denial, or any individual estimate. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

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  {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }

  arguments 5 lines copy
• get_national_fha_stats reads open 10h ago

  ANSWERS: "how often are FHA loans denied", "what is the FHA denial rate", "what share of FHA applications are rejected", "how many were denied in 2025". Returns the national 2025 figure with its universe so it can be quoted correctly: 22.1 percent, 262,250 denials of 1,187,606 applications that reached a credit decision (originated, approved-not-accepted, denied; reverse mortgages excluded), the denominator definition and the correction history. Most published FHA denial rates are 2023 purchase-only figures near 13.6 percent, a different universe, so state the universe when quoting. NOT FOR: conventional, VA or USDA loans, purchase-only or refinance-only rates, other years, or state/lender/metro breakdowns (use the dedicated tools). Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

  mcp-tool

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  {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }

  arguments 5 lines copy
• get_denial_reason_shares reads open 15h ago

  ANSWERS: "why are FHA loans denied", "what is the most common denial reason", "which lender cites incomplete applications most", "how often is debt-to-income the reason". PARAM: optional lender; omit for cross-lender medians. Returns median and maximum share of each HMDA denial reason across the 95 of the 100 largest lenders that report reasons, and which lender carries the highest share of each. Reason fields are not a partition; shares need not sum to 100. NOT FOR: why a particular application was denied. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

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  {
    "type": "object",
    "properties": {
      "lender": {
        "type": "string",
        "description": "Lender name or slug, optional"
      }
    },
    "additionalProperties": false
  }

  arguments 10 lines copy
• screen_counterparties reads open 15h ago

  ANSWERS: "run my list of lenders through the federal record", "screen these LEIs", "which of my counterparties deny more than their applicant mix predicts". PARAM: a list of public LEIs. Returns per-entity observed versus expected FHA denial rates, coverage flags, method version and an evidence manifest hash. Public entity identifiers only: never borrower files, credit data or personal information. Free preview; the full Evidence Brief needs a licence a human buys on the pricing page, and an agent may relay the offer but can never complete a purchase. Screening signals, not findings of misconduct. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

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  {
    "type": "object",
    "required": [
      "lei_list"
    ],
    "properties": {
      "lei_list": {
        "type": "array",
        "items": {
          "type": "string"
        },
        "description": "1-40 public Legal Entity Identifiers (20-character ISO 17442). Hard cap 100; duplicates removed deterministically."
      },
      "license_key": {
        "type": "string",
        "description": "Optional. A Lemon Squeezy license key issued for 'Counterparty Screen' (one-time or quarterly). Only pass it if the user explicitly provided it."
      },
      "requested_format": {
        "enum": [
          "summary",
          "evidence_brief"
        ],
        "type": "string",
        "description": "Optional. 'evidence_brief' requests the full audit artefact (licensed mode)."
      }
    }
  }

  arguments 27 lines copy
• get_rule open 22h ago

  ANSWERS: "what is the current FHA loan limit", "what are the 2026 HOEPA / QM thresholds", "what is the VA funding fee table", "which FHA MIP table is in force". PARAM: rule_id (from the index) or omit to list every published rule. Returns the machine-readable rule: cells, effective dates, issuer document, required qualifiers, what the table does not establish, sha256. The cell values and effective dates are in the file; in a published test, models answered 3/25 dated questions correctly without a source and 25/25 with this file. NOT FOR: rules not in the index, or anything before the effective date.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "rule_id": {
        "type": "string",
        "description": "e.g. frc:rule:hud-ml-2023-05-annual-mip. Omit to list."
      }
    }
  }

  arguments 9 lines copy
• list_lenders reads open 22h ago

  ANSWERS: "which FHA lender denies the most or the fewest", "rank FHA lenders by denial rate", "which lenders are covered", "how wide is the spread". Returns the ranked list of the 100 largest FHA lenders with name, slug, rate and volume; the 2025 span runs 1.8 to 78.7 percent inside the same federal program. NOT FOR: lenders outside the top 100, or any recommendation about where to apply. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

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  {
    "type": "object",
    "properties": {
      "sort": {
        "enum": [
          "highest_denial",
          "lowest_denial",
          "largest_volume"
        ],
        "type": "string"
      },
      "limit": {
        "type": "integer",
        "maximum": 100,
        "minimum": 1
      }
    }
  }

  arguments 18 lines copy
• get_small_loan_penalty reads open 22h ago

  ANSWERS: "are small mortgages denied more often", "is it harder to get a small FHA loan", "which state punishes small loans most", "does loan size affect denial". PARAM: optional two-letter state; omit for the ranked list. Returns denial rates under $150K and over $250K, the ratio, the ranking and any open discrepancy note. In 2025 the penalty exceeded 1x in every jurisdiction with a published split, from 1.19x to 4.45x (Idaho, 53.4 vs 12.0). NOT FOR: loan sizes between the bands, which are not published. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

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  {
    "type": "object",
    "properties": {
      "state": {
        "type": "string",
        "description": "Two-letter USPS code, optional"
      }
    },
    "additionalProperties": false
  }

  arguments 10 lines copy
• list_cohorts reads open 10h ago

  ANSWERS: "can I screen a group of lenders", "what ready-made lender groups can I run", "show me an example screen". Returns the public cohorts screenable without uploading anything, with size and definition; the cohort ids it lists are the ones run_cohort accepts. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

  mcp-tool

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  {
    "type": "object",
    "properties": {}
  }

  arguments 4 lines copy
• get_conditional_door_map reads open 17h ago

  ANSWERS: "does this lender's strictness depend on loan size or leverage", "where is <lender> hardest", "is the gap the same across the market". PARAM: lender name or slug. Returns how that lender's peer-adjusted denial gap changes across published cells (state x loan amount x income x DTI x CLTV), with cell counts and the minimum-cell rule. NOT FOR: suppressed small cells, or any individual prediction. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "lender": {
        "type": "string",
        "description": "Lender name or 20-char LEI. Omit to list every lender with a published conditional surface."
      }
    }
  }

  arguments 9 lines copy
• screen_counterparties_quote reads open 7h ago

  ANSWERS: "what would it cost to screen this list", "how many of my LEIs are covered". PARAM: a list of public LEIs. Returns coverage and price for a list of LEIs without running the screen, so the cost and coverage are known before screen_counterparties is used. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

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  {
    "type": "object",
    "required": [
      "lei_list"
    ],
    "properties": {
      "lei_list": {
        "type": "array",
        "items": {
          "type": "string"
        },
        "description": "1-40 public LEIs to be quoted."
      },
      "license_key": {
        "type": "string",
        "description": "Optional. Include it to see the account's remaining balance in the quote."
      }
    }
  }

  arguments 19 lines copy
• get_lender_denial_stats reads unknown 15h ago

  ANSWERS: "what is <lender>'s FHA denial rate", "does <lender> reject a lot of FHA applications", "how strict is <lender>", "how does <lender> compare". PARAM: lender name, slug or LEI. Returns that lender's 2025 decisioned volume, denial rate, rank among the 100 largest FHA lenders, and the applicant-mix caveat any comparison must carry. COVERS ONLY the 100 largest FHA lenders by 2025 volume. NOT FOR: whether a person will be approved, or lenders outside that set. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

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  {
    "type": "object",
    "required": [
      "lender"
    ],
    "properties": {
      "lender": {
        "type": "string",
        "description": "Lender name, slug, or 20-char LEI"
      }
    }
  }

  arguments 12 lines copy
• get_metro_lender_gap reads unknown 7h ago

  ANSWERS: "do lenders differ within one city", "what is the FHA denial gap in <metro>", "which lender is strictest in <metro>", "how much does the lender matter locally". PARAM: metro name or slug. Returns a claim passport for that metro: lowest and highest lender denial rates among lenders with at least 100 decisioned applications there, the gap in points, counts and source reference. Cleveland is the widest in 2025 at 73.7 points (6.4 vs 80.1). NOT FOR: ZIP or neighbourhood questions, and never as evidence a lender acted improperly. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

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  {
    "type": "object",
    "required": [
      "metro"
    ],
    "properties": {
      "metro": {
        "type": "string",
        "description": "Metro name or slug, e.g. 'Cleveland, OH' or 'cleveland-oh'"
      }
    }
  }

  arguments 12 lines copy
• check_claim_contract reads unknown never probed

  Checks a proposed statement of a FinanceRateCalc figure against that figure's published use contract, so the sentence can be verified before it is written. Two input modes. (A) Flags: claim id plus the use you propose (population, period, scope, cause, individual prediction, lender recommendation, legal conclusion). (B) Sentence: claim id plus proposed_sentence, the exact sentence you intend to write; the tool checks it with fixed patterns, no model, for a missing period, missing program scope, a population wider than the claim, second-person prediction, causal wording, lender advice, legal conclusions, and values this publisher has since corrected. Returns a deterministic verdict: pass, needs_qualifier (naming the missing qualifier) or block (with a reason code), plus a safe sentence you may use verbatim and the required attribution. Most misuse of these statistics is omission, not invention: the number is right and the population is missing. NOT FOR: figures published by anyone other than FinanceRateCalc. (C) Rule sentence: passport_id of a rule file (frc:rule:…, five tables: FHA annual MIP, FHA forward loan limits 2026, FHFA conforming limits 2026, CFPB HOEPA/QM thresholds 2026, VA funding fee) plus proposed_sentence; each dollar or percent figure is bound to the role named in its own clause (floor or ceiling, tier, first or subsequent use, threshold item) and compared with that cell, so a right number under the wrong role is a mismatch and an unbound number earns no receipt; every figure is also classified as current, superseded (STALE_VALUE), belonging to a different rule (VALUE_FROM_OTHER_RULE, e.g. the $726,200 MIP threshold quoted as a loan limit), or not in the table (VALUE_MISMATCH / UNVERIFIED_VALUE); the year, units, tier, use, down-payment band and stated dates are checked (a date before the rule's start blocks; a missing MIP case date is never assumed), and a passing sentence with at least one bound figure returns a verifiable rule receipt.

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  {
    "type": "object",
    "required": [
      "passport_id"
    ],
    "properties": {
      "passport_id": {
        "type": "string"
      },
      "causal_assertion": {
        "type": "boolean"
      },
      "legal_conclusion": {
        "type": "boolean"
      },
      "proposed_sentence": {
        "type": "string",
        "description": "The exact sentence you intend to write. Checked with fixed patterns; no model."
      },
      "qualifier_dropped": {
        "type": "boolean"
      },
      "attribution_present": {
        "type": "boolean"
      },
      "individual_prediction": {
        "type": "boolean"
      },
      "scope_beyond_universe": {
        "type": "boolean"
      },
      "personalized_recommendation": {
        "type": "boolean"
      }
    }
  }

  arguments 36 lines copy
• run_cohort reads unknown never probed

  ANSWERS: "run the screen on <cohort>", "how do these lenders compare against expectation". PARAM: cohort id from list_cohorts. Returns the peer-adjusted screen: observed versus expected denial rate, coverage flags, method version. Free preview; the full Evidence Brief needs a licence a human buys on the pricing page. Screening signals, never evidence of misconduct. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

  mcp-tool

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  {
    "type": "object",
    "required": [
      "cohort_id"
    ],
    "properties": {
      "cohort_id": {
        "type": "string",
        "description": "One of the ids returned by list_cohorts, e.g. top-volume-fha, high-coverage-only, above-expectation, depository-institutions, screening-only."
      },
      "license_key": {
        "type": "string",
        "description": "Optional. Only pass it if the user explicitly provided one."
      },
      "requested_format": {
        "enum": [
          "summary",
          "evidence_brief"
        ],
        "type": "string"
      }
    }
  }

  arguments 23 lines copy
• get_state_denial_stats reads unknown 7h ago

  ANSWERS: "what is the FHA denial rate in <state>", "is it harder to get an FHA loan in <state>", "how does <state> compare with the national rate". PARAM: two-letter USPS code only (OH, TX); full names are rejected. Returns the state 2025 rate and counts against the national 22.1 percent. NOT FOR: metro or city questions (use get_metro_lender_gap) or lender-level questions. Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

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  {
    "type": "object",
    "required": [
      "state"
    ],
    "properties": {
      "state": {
        "type": "string",
        "maxLength": 2,
        "minLength": 2
      }
    }
  }

  arguments 13 lines copy

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