Supabase
MCP server for interacting with the Supabase platform
제작자가 쓴 설명(영어 원문)
2025 HMDA FHA denial statistics and dated US mortgage rule tables, with verifiable receipts.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://frc-mcp.ziyetis.workers.devClaude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"frc": {
"command": "npx",
"args": [
"-y",
"frc-mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add --transport http frc https://frc-mcp.ziyetis.workers.devclaude mcp add frc -- npx -y frc-mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"frc": {
"url": "https://frc-mcp.ziyetis.workers.dev"
}
}
}프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"frc": {
"command": "npx",
"args": [
"-y",
"frc-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"frc": {
"type": "http",
"url": "https://frc-mcp.ziyetis.workers.dev"
}
}
}프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"frc": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"frc-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://frc-mcp.ziyetis.workers.dev메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
도구 이름과 설명은 서버가 2026년 11월 7일에 알려 준 그대로예요. 우리가 아니라 제작자가 쓴 글이고, 일반 텍스트로만 보여 드려요.
check_claim_contractChecks 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, lend
get_national_fha_statsANSWERS: "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 ap
get_lender_denial_statsANSWERS: "what is 's FHA denial rate", "does reject a lot of FHA applications", "how strict is ", "how does 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 a
get_application_outcomesANSWERS: "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 's FHA applications end". Returns the five HMD
list_lendersANSWERS: "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 ins
get_small_loan_penaltyANSWERS: "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 rati
get_denial_reason_sharesANSWERS: "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 r
get_state_denial_statsANSWERS: "what is the FHA denial rate in ", "is it harder to get an FHA loan in ", "how does 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: met
get_door_effect_summaryANSWERS: "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 outcom
get_metro_lender_gapANSWERS: "do lenders differ within one city", "what is the FHA denial gap in ", "which lender is strictest in ", "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 wit
screen_counterpartiesANSWERS: "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
screen_counterparties_quoteANSWERS: "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 observ
list_cohortsANSWERS: "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 obse
run_cohortANSWERS: "run the screen on ", "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 h
get_conditional_door_mapANSWERS: "does this lender's strictness depend on loan size or leverage", "where is 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
get_ruleANSWERS: "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, effecti
resolve_fha_annual_mipANSWERS: "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
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
레지스트리 이름이 GitHub 계정 financeratecalc 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
126ms 만에 응답(HTTP 200)
로그인 필요 없음
도구 설명 17개를 읽었고, AI에게 보내는 숨겨진 지시는 없었어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 3개 중 3개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
둘 다 가능해요. 내 컴퓨터에 설치해도 되고, 클라우드 버전에 연결해도 돼요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.44.0)은 어제 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: Supabase, MongoDB MCP Server, Elasticsearch MCP Server
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP server for interacting with the Supabase platform
MongoDB Model Context Protocol Server
MCP server for interacting with Elasticsearch
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Read-only statistics over the complete 2025 US HMDA mortgage record (1,187,606 FHA credit decisions, reverse mortgages excluded) plus dated, machine-readable US mortgage rule tables, served to AI agents over MCP. Every figure returns with its period, population and program scope, a use contract, and a receipt that can be verified later.
The red line: every figure is a historical aggregate. This server never accepts borrower details and never returns an individual approval prediction.
https://frc-mcp.ziyetis.workers.dev
Streamable HTTP, stateless. MCP protocol revisions 2026-07-28, 2025-11-25, 2025-06-18, 2025-03-26. Server version 1.44.0 (tools, resources and prompts; A2A agent card at /.well-known/agent-card.json; a citation envelope on every figure-bearing result; every claim document carries a keyless CFPB Data Browser reproduce query). Listed in the official MCP registry as io.github.financeratecalc/frc-mcp.
Client configs (Claude Desktop, Claude Code, Cursor, VS Code, Windsurf, Codex, Gemini CLI), an instruction block for CLAUDE.md / AGENTS.md, and a first task to try: https://financeratecalc.com/use-frc.html
| Tool | What it answers |
|---|---|
check_claim_contract | Checks a sentence you intend to write against the figure's use contract; fixed patterns, no model. Returns pass / needs_qualifier / block, a safe wording, and a receipt on pass. Also checks sentences against the five rule tables, binding each figure to the role named in its clause. |
get_national_fha_stats | 2025 national FHA denial rate with its universe. |
get_lender_denial_stats | One of the 100 largest FHA lenders: volume, denial rate, rank, applicant-mix caveat. |
list_lenders | The 100 largest FHA lenders ranked by denial rate or volume. |
get_state_denial_stats | State FHA denial rate and small-loan split. |
get_metro_lender_gap | Within one metro, the spread between the highest- and lowest-denying high-volume lenders. |
get_small_loan_penalty | Denial rate under $150K vs over $250K, by state. |
get_denial_reason_shares | Median and maximum share of each HMDA denial reason across the top-100 lenders. |
get_door_effect_summary | Lender identity's share of explained variation in 2025 FHA denials. |
get_application_outcomes | Where FHA applications end: originated, approved-not-accepted, denied, withdrawn, closed-incomplete as shares of applications acted on, nationally or for one lender, with the reconciliation to the decisioned denial rate. |
get_conditional_door_map | Per-lender conditional surface with its robustness record. |
list_cohorts / run_cohort | Ready-made public cohorts; no upload needed. |
get_rule | One of five dated rule tables: FHA annual MIP (ML 2023-05), FHA forward loan limits 2026, FHFA conforming limits 2026, CFPB HOEPA/QM thresholds 2026, VA funding fee. |
resolve_fha_annual_mip | The MIP cell for a stated term, base loan amount and LTV; asks for a missing condition instead of guessing it. |
screen_counterparties / screen_counterparties_quote | Counterparty screen; free preview, full brief needs a licence bought by a human. The agent only relays the offer. |
Plain HTTP beside MCP: GET /server-card, GET /cite/ (receipted sentence in text, Markdown, HTML and BibTeX), GET /verify?r= (is this figure still current; if not, which correction superseded it).
A figure travels with a receipt such as ⟦FRC:national-fha-denial-rate-2025:22.1%:ebf6b00b:m2610⟧: claim id, value, the first eight hex characters of a hash of the claim object, and the channel and month it was issued through. /verify answers current, stale (corrected since; the correction is returned), hash-current-value-mismatch (the quoted value was edited) or unrecognized (this publisher never issued it). Conformance runs on every deploy and is published: https://financeratecalc.com/conformance.html
The frc-mcp npm package is the original five read-only tools from a bundled data snapshot; it does not carry the rule tables, the sentence gate or receipts. Prefer the remote endpoint.
{
"mcpServers": { "financeratecalc": { "command": "npx", "args": ["-y", "frc-mcp"] } } }
The remote server's source of record is worker/index.js in https://github.com/financeratecalc/financeratecalc.github.io, deployed to Cloudflare Workers on every change to that file. remote/worker.js in this repository is an early (five-tool) copy kept for reference.
Data: CC BY 4.0, attribution to financeratecalc.com. Source of truth: public CFPB HMDA 2025 (loan_type 2; actions 1, 2, 3; denial = action 3). Method: https://financeratecalc.com/methodology.html · corrections log: https://financeratecalc.com/corrections.html · SSRN 7156938. No lender recommendations, no individual predictions, no lender pays for placement.