# US Loan and Mortgage Rates: Current and History (`scrapemint/us-loan-mortgage-rates`) Actor

What Americans borrow at: 30 and 15 year mortgage rates, bank prime, credit card APR, new car loans and personal loans from the Federal Reserve, with weekly, monthly and yearly changes and where each rate sits in its own range. Keyless, no browser and no proxy.

- **URL**: https://apify.com/scrapemint/us-loan-mortgage-rates.md
- **Developed by:** [Ken M](https://apify.com/scrapemint) (community)
- **Categories:** Business, News
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## US Loan and Mortgage Rates

What Americans actually borrow at, straight from the Federal Reserve: 30 and 15 year mortgage rates, the bank prime rate, credit card APR, new car loans and personal loans, plus national house prices so you can see borrowing costs and home values together.

Every rate arrives with context rather than a bare number: how it moved over the past week, month and year, and where it sits inside its own multi year range.

No login, no API key, no proxy.

### What you get

One row per rate in `latest` mode:

```json
{
  "seriesId": "MORTGAGE30US",
  "label": "30-year fixed mortgage",
  "category": "mortgage",
  "rate": 6.66,
  "unit": "percent per year",
  "observationDate": "2026-07-30",
  "frequency": "weekly",
  "changeWeek": 0.08,
  "changeMonth": 0.17,
  "changeYear": -0.08,
  "percentileRank": 63,
  "windowYears": 5,
  "windowLow": 2.77,
  "windowHigh": 7.79,
  "windowMedian": 6.81,
  "isStale": false,
  "daysSinceObservation": 5
}
```

In `history` mode you get one row per published observation instead, going back as far as the series runs. The 30 year mortgage starts in 1971.

### Rates covered

| Series | Rate | Published |
| --- | --- | --- |
| `MORTGAGE30US` | 30 year fixed mortgage | weekly |
| `MORTGAGE15US` | 15 year fixed mortgage | weekly |
| `DPRIME` | Bank prime loan rate | daily |
| `DFF` | Federal funds effective rate | daily |
| `TERMCBCCALLNS` | Credit card interest rate | quarterly |
| `TERMCBAUTO48NS` | 48 month new car loan | quarterly |
| `RIFLPBCIANM60NM` | 60 month new car loan | quarterly |
| `TERMCBPER24NS` | 24 month personal loan | quarterly |

House prices, so a single run answers what a home costs as well as what it costs to borrow:

| Series | Measure | Published |
| --- | --- | --- |
| `CSUSHPINSA` | Case-Shiller national home price index | monthly |
| `MSPUS` | Median sale price of houses sold | quarterly |
| `ASPUS` | Average sale price of houses sold | quarterly |

These are not percentages. Case-Shiller is an index where January 2000 equals 100, and the sale prices are US dollars, so every row carries its own `unit` and values must never be averaged or ranked across different units.

Two more, `MORTGAGE5US` and `MMNRNJ`, are no longer published. They still return their final value, so they are left out unless you ask for them and always come back marked `isStale`.

### Input

| Field | Description |
| --- | --- |
| `mode` | `latest` (default) or `history` |
| `series` | Which rates to return. Empty means all current ones |
| `includeDiscontinued` | Include the two retired series (default false) |
| `percentileYears` | Window for the low, high, median and percentile (default 5) |
| `historyFrom` / `historyTo` | History mode date range, `YYYY-MM-DD` |
| `maxRows` | Total rows returned (default 500) |

### Examples

Today's rates with context:

```json
{ "mode": "latest" }
```

Just the mortgage rates:

```json
{ "mode": "latest", "series": ["MORTGAGE30US", "MORTGAGE15US"] }
```

Two years of weekly 30 year mortgage history:

```json
{ "mode": "history", "series": ["MORTGAGE30US"], "historyFrom": "2024-08-01" }
```

### How the numbers are worked out

A change is measured against the newest observation at or before that date, not a fixed number of rows back, because these series publish at different rhythms.

A change window shorter than how often the rate is published comes back as `null`. The credit card and loan surveys are quarterly, so there is no such thing as their weekly move, and reporting one would be inventing a measurement.

Any rate that is missing for a period, such as a daily series over a holiday, is left out rather than treated as zero. A zero would read as a real 0.00% rate.

`isStale` compares the age of the newest observation against how often that rate is normally published, so a quarterly survey is not called stale for behaving quarterly.

### Who it's for

Anyone tracking borrowing costs: mortgage and lending sites showing current rates, personal finance tools and newsletters, fintech dashboards, and analysts watching what consumer credit costs. Pairs with the **US Treasury Rates Scraper** and **Central Bank Policy Rates** for the wholesale and policy side of the same picture.

### Pricing

Pay per rate row. The first 2 rows of every run are free so you can validate the output before you pay.

# Actor input Schema

## `mode` (type: `string`):

latest = one row per rate with change and range context. history = one row per published observation.

## `series` (type: `array`):

Which series to return. Leave empty for all current ones. Rates: MORTGAGE30US, MORTGAGE15US, DPRIME, DFF, TERMCBCCALLNS, TERMCBAUTO48NS, RIFLPBCIANM60NM, TERMCBPER24NS. House prices: CSUSHPINSA (Case-Shiller index), MSPUS (median sale price), ASPUS (average sale price). Plus the discontinued MORTGAGE5US and MMNRNJ. House prices are not percentages, so read the unit on each row.

## `includeDiscontinued` (type: `boolean`):

Two series are no longer published but still return their final value. They are excluded by default; when included they are always marked isStale.

## `percentileYears` (type: `integer`):

How far back to look when working out the low, high, median and percentile rank for each rate.

## `historyFrom` (type: `string`):

History mode only. Earliest observation date, YYYY-MM-DD. Empty means from the start of the series.

## `historyTo` (type: `string`):

History mode only. Latest observation date, YYYY-MM-DD.

## `maxRows` (type: `integer`):

Total rows to return.

## Actor input object example

```json
{
  "mode": "latest",
  "series": [
    "MORTGAGE30US",
    "CSUSHPINSA",
    "MSPUS"
  ],
  "includeDiscontinued": false,
  "percentileYears": 5,
  "historyFrom": "2024-01-01",
  "historyTo": "2026-08-01",
  "maxRows": 500
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "series": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/us-loan-mortgage-rates").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "series": [] }

# Run the Actor and wait for it to finish
run = client.actor("scrapemint/us-loan-mortgage-rates").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "series": []
}' |
apify call scrapemint/us-loan-mortgage-rates --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapemint/us-loan-mortgage-rates"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ulW1HgMWdQnkgSDvm/builds/H8ad9V1do41ti00zQ/openapi.json