# Address Normalizer (`parseforge/address-normalizer`) Actor

Normalizes addresses from a list or CSV file into standardized components like street, city, state, ZIP, and country. Supports custom normalization rules.

- **URL**: https://apify.com/parseforge/address-normalizer.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** AI, Automation, Developer tools
- **Features:** Limited permissions
- **Stats:** 26 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $9.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

[![ParseForge](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner-v4.webp)](https://apify.com/parseforge?fpr=vmoqkp)

### Address Normalizer

**Normalize messy address lists into clean, standardized records.** Feed raw addresses or a CSV file and get back structured components like street, city, state, ZIP, and country. No geocoding API key required.

Address data arrives dirty: inconsistent casing, missing ZIP codes, abbreviations, and typos. This Actor cleans and standardizes each address into a consistent format, ready for CRM imports, mailing lists, or analytics. It accepts a list of addresses or a CSV file and returns normalized fields for every input.

| Who uses it | What they scrape Address Normalizer for |
|---|---|
| Data analysts | Cleaning address columns before joining datasets or running reports |
| Marketing teams | Preparing mailing lists for direct mail campaigns |
| CRM administrators | Deduplicating and standardizing customer address records |
| E-commerce managers | Validating shipping addresses before order fulfillment |

### What it does

This Actor normalizes addresses from a list or CSV file and returns each address as a structured object with standardized components.

- 📋 **List input:** paste addresses directly, one per line, or as JSON objects with address fields
- 📁 **CSV file input:** upload a CSV or provide a URL; the Actor reads an 'address' column or component columns
- 🧹 **Default normalization:** standardizes casing, expands common abbreviations, and fills missing ZIP codes when possible
- ✏️ **Custom prompt:** provide your own normalization rules to override defaults

Results export to CSV, JSON, Excel, or XML, or straight from the API.

### What you can do with Address Normalizer data

**🧹 Clean CRM data.**

A sales ops manager uploads a CSV of 10,000 customer addresses and gets back standardized fields to merge duplicate records.

**📬 Prepare mailing lists.**

A direct mail agency normalizes client address lists to meet USPS formatting guidelines before printing.

**📊 Improve analytics.**

A data analyst normalizes address fields from multiple sources to enable accurate geographic segmentation.

**🚚 Validate shipping addresses.**

An e-commerce store normalizes checkout addresses to reduce failed deliveries and returned packages.

### Why choose this scraper

|  | What you get |
|---|---|
| **No API key** | Works without external geocoding services |
| **Batch processing** | Handles thousands of addresses in one run |
| **Flexible input** | Accepts strings, objects, or CSV files |
| **Customizable** | Override default rules with your own prompt |

### How it compares

This Actor focuses on address normalization, while the competitor listed below extracts transcripts from Instagram Reels, a different data type.

| Feature | ParseForge | Instagram AI Transcript Extractor |
|---|---|---|
| Address normalization | Yes | Not listed |
| CSV file input | Yes | Not listed |
| Custom normalization rules | Yes | Not listed |
| Returns structured address components | Yes | Not listed |
| No API key required | Yes | Not listed |

### Configure the run

Provide addresses as a list or CSV file, and optionally supply a custom prompt to control normalization rules. The Input tab lists every parameter.

A first run with the defaults:

```json
{
  "addresses": [
    "123 main st new york ny 10001",
    "456 oak avenue los angeles ca",
    "789 pine road chicago il 60601"
  ]
}
```

### Pricing

Pay-per-result: **$0.015 per result** collected. You pay only for the results written to your dataset.

| Results collected | Approximate cost |
|---|---|
| 100 results | $1.50 |
| 1,000 results | $15.00 |
| 10,000 results | $150.00 |

New Apify accounts start with $5 in free credit.

### Free users

Free-plan runs return up to 10 results as a preview. [Upgrade your Apify plan](https://console.apify.com/sign-up?fpr=vmoqkp) to collect up to 1,000,000 results per run.

### Run it

1. [Create a free Apify account with $5 in credit](https://console.apify.com/sign-up?fpr=vmoqkp).
2. Open the [Address Normalizer](https://apify.com/parseforge/address-normalizer?fpr=vmoqkp).
3. Set your inputs and any filters, then click **Start**.
4. Export the results as CSV, Excel, JSON, or XML from the **Dataset** tab.

Run it programmatically through the [Apify API](https://docs.apify.com/api/v2) (`run-sync-get-dataset-items`) or the [ApifyClient](https://docs.apify.com/api/client/js) for JavaScript and Python.

### Use with AI agents (MCP)

Give an AI agent live access to Address Normalizer through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

```bash
claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/address-normalizer"
```

Then prompt it in plain language to run the scraper and read back the results.

### Troubleshooting

**Why am I getting no results?**

Make sure you provided addresses in the 'addresses' field or a valid CSV file. If both are empty, the Actor has nothing to process.

**Why are some addresses not normalized correctly?**

The default rules may not cover all edge cases. Try providing a custom prompt with specific instructions for those addresses.

**Why does my CSV file fail to load?**

Ensure the CSV is publicly accessible if using a URL, and that it has the expected columns. For uploaded files, check the file format and encoding.

**Why is the run taking so long?**

Large address lists can take time. Consider splitting the input into smaller batches or using a CSV file for more efficient processing.

**Why do I see duplicate addresses in the output?**

The Actor does not deduplicate by default. If you need deduplication, provide a custom prompt or post-process the results.

### FAQ

| Question | Answer |
|---|---|
| What address formats does this Actor support? | It accepts free-form strings like '123 main st new york ny 10001' as well as structured objects with fields like street, city, state, zip, and country. CSV files can have a single 'address' column or separate component columns. |
| Does this Actor geocode addresses to latitude and longitude? | No, it only normalizes the address text into standardized components. It does not return coordinates. |
| Can I use my own normalization rules? | Yes, provide a custom prompt in the input and the Actor will apply your instructions instead of the default rules. |
| How many addresses can I process in one run? | There is no hard limit, but very large lists may take longer. For best performance, use a CSV file for bulk input. |
| What does the output look like? | Each input address is returned as an object with normalized fields such as street, city, state, postal code, and country, along with the original input for reference. |
| Does it work with international addresses? | The default rules are optimized for US addresses, but you can provide a custom prompt to handle other countries. |
| Can I provide a CSV file from a URL? | Yes, the csvFile input accepts either an uploaded file or a URL to a publicly accessible CSV. |
| What if my CSV has different column names? | The Actor expects an 'address' column or columns named street, city, state, zip, and country. If your columns differ, rename them before uploading or use a custom prompt to map them. |
| Is there a way to preview the normalization before running the full job? | You can run a small test with a few addresses to see the output format before processing a large file. |
| Does this Actor store my address data? | Apify stores the results in your dataset, but you can delete them after the run. The Actor itself does not retain data beyond the run. |

### Related actors

Browse the full [ParseForge collection](https://apify.com/parseforge?fpr=vmoqkp) for more scrapers.

🆘 **Need help?** Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ **Disclaimer.** This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Address Normalizer. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.

# Actor input Schema

## `addresses` (type: `array`):

List of addresses to normalize. Each address can be a string or an object with address fields. You can also provide a CSV file URL instead.

## `csvFile` (type: `string`):

Upload a CSV file containing addresses, or provide a URL to a CSV file. The CSV should have an 'address' column or columns for address components (street, city, state, zip, country). If provided, addresses array will be ignored.

## `customPrompt` (type: `string`):

Optional custom instructions for address normalization. If not provided, default normalization rules will be used.

## Actor input object example

```json
{
  "addresses": [
    "123 main st new york ny 10001",
    "456 oak avenue los angeles ca",
    "789 pine road chicago il 60601"
  ]
}
```

# Actor output Schema

## `overview` (type: `string`):

Overview view of normalized addresses with key fields displayed in a table format

## `addresses` (type: `string`):

Complete dataset with all normalized addresses including original address, normalized address, and all address components

# 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 = {
    "addresses": [
        "123 main st new york ny 10001",
        "456 oak avenue los angeles ca",
        "789 pine road chicago il 60601"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/address-normalizer").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 = { "addresses": [
        "123 main st new york ny 10001",
        "456 oak avenue los angeles ca",
        "789 pine road chicago il 60601",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("parseforge/address-normalizer").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 '{
  "addresses": [
    "123 main st new york ny 10001",
    "456 oak avenue los angeles ca",
    "789 pine road chicago il 60601"
  ]
}' |
apify call parseforge/address-normalizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,parseforge/address-normalizer"
        }
    }
}
```

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/4PceldtFISxFiz7ha/builds/Fx3IDql2ia6y491KT/openapi.json