# 99.co Scraper (`one-api/99co-scraper`) Actor

Scrape 99.co Singapore property listings. Search by location, coordinates, polygon, or 99.co URL; pull enriched property details (similar listings, nearby amenities, floor plans, project analysis) by listing id or URL; and look up agents from the public directory.

- **URL**: https://apify.com/one-api/99co-scraper.md
- **Developed by:** [ONE API](https://apify.com/one-api) (community)
- **Categories:** Lead generation, Real estate
- **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 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.

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

## 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

## 99.co Scraper

Scrape **99.co Singapore** property listings — residential and commercial. Search by location, coordinates, polygon, or 99.co URL; pull **enriched property details** (similar listings, nearby amenities, floor plans, project analysis) by listing id or URL; and look up **agents** from the public directory.

### What it does

- **4 search modes** — auto-detected per line:
  - Location name (MRT station, neighbourhood, district, project — e.g. `Orchard`, `Tampines`)
  - Coordinates `lat,lng` or `lat,lng,radius_m` (e.g. `1.3042,103.8324,1500`)
  - Polygon — 3+ space-separated `lat,lng` pairs (e.g. `1.30,103.82 1.32,103.82 1.32,103.85`)
  - A `https://www.99.co/...` search URL
- **Property Details** — listing id (e.g. `EVPssE5S3KHLKudeJdhwT4`) or 99.co listing URL. Each record is **enriched** with `similarListings`, `nearbyAmenities`, `floorPlans`, and `projectAnalysis` (nearest MRT / schools / supermarkets, facilities) — all kept in the `Raw` column. Toggle `enrich` off for a leaner, faster call.
- **Agents** — keyword search of the public agent directory (use `*` to browse all), plus full agent profiles by slug or profile URL (contact info, agency, listings breakdown).
- **Location Autocomplete** — resolve free text into 99.co location ids, types, and coordinates (MRT stations, districts, projects, schools).

### Filters

Listing type (sale / rent), segment (residential / commercial), property type (HDB / condo / landed / retail / office / industrial / land), price range, bedrooms, bathrooms, floor area — plus an advanced free-form filter field for tenure, furnishing, floor level, property status (resale / new launch / subsale), building age, keywords, and more. Filters apply to every search line.

### Output

- **One flat dataset row per result** — sortable, filterable, CSV-exportable.
- Columns: `Mode`, `Input Given`, `ID`, `Title`, `Type`, `Price`, `PSF`, `Bedrooms`, `Bathrooms`, `Floor Area (sqft)`, `Address`, `District`, `Tenure`, `Built Year`, `Status`, `Posted`, `Agent Name`, `Agent Phone`, `Agency`, `Photo`, `URL`.
- Full upstream JSON kept in the `Raw` column for power users (including all enrichment blocks on property details).

### Inputs

- Each section is independent — fill only the ones you need.
- Multiple inputs per section: one per line.
- `Pages per search` × `Results per page` (max 60) control how many listings each search line returns; pagination stops early when 99.co runs out of results.

### Pricing

- Pay per result: **$3 per 1,000 dataset items** — same rate on every Apify plan tier.
- Apify start fee: $0.00005 per run.

### Notes

- **Singapore only.** 99.co Indonesia runs on a separate platform and is not covered.
- Prices are in **SGD**; areas in sqft.
- Agent search returns each agent's `slug` — feed it into the *Agent slug or profile URL* field for the full profile.
- Sorting: 99.co's API supports distance-based sorting only (`sortOrder=distance` via the advanced filter field); default order is relevance.

### Errors

- Failures land in the dataset as rows with `Mode = "ERROR"` and the upstream error message in the `Status` column — nothing is silently dropped.

# Actor input Schema

## `search_inputs` (type: `array`):

Auto-detects each entry and routes to the right `/search/*` endpoint:
• `https://www.99.co/...` search URL → `/search/byurl`
• `lat,lng` or `lat,lng,radius_m` (e.g. `1.3042,103.8324,1500`) → `/search/bycoordinates`
• 3+ space-separated `lat,lng` pairs (e.g. `1.30,103.82 1.32,103.82 1.32,103.85`) → `/search/bypolygon`
• Anything else — MRT station, neighbourhood, district, project name (e.g. `Orchard`, `Tampines`) → `/search/bylocation`

Filters below apply to every search call. Each hit returns one dataset row per listing.

## `searchType` (type: `string`):

Sale or rental listings.

## `propertySegment` (type: `string`):

Residential (HDB / condo / landed) or commercial (retail / office / industrial / land).

## `propertyType` (type: `string`):

Main category. `hdb` / `condo` / `landed` need segment = Residential; `retail` / `office` / `industrial` / `land` need segment = Commercial.

## `priceRange` (type: `string`):

Format: `min:500000,max:3000000` — or just `min:500000` / `max:3000000`.

## `bedrooms` (type: `string`):

Comma-separated counts, e.g. `2,3` for 2- and 3-bedroom listings.

## `bathrooms` (type: `string`):

Comma-separated counts, e.g. `2`.

## `floorAreaRange` (type: `string`):

Format: `min:600,max:2000`.

## `moreFilters` (type: `string`):

Optional query-string of extra filters merged into every search, e.g. `furnishing=fully&tenure=freehold&floorLevel=high&propertyStatus=resale`. Supported keys include: `propertyStatus` (resale/new\_launch/subsale), `tenure` (freehold/leasehold), `furnishing` (fully/partial/unfurnished), `floorLevel` (ground/low/mid/high/top/penthouse), `rentalType` (unit/room), `roomType` (master/common), `buildingAge` (5/10/20), `keywords`, `hasFloorPlan`, `condoSubType`, `landedSubType`, `hdbSubType`, `landSizeRange`, `completionYearRange`.

## `pages` (type: `integer`):

How many pages to fetch for each search query (stops early when 99.co runs out of results).

## `resultCount` (type: `integer`):

99.co caps each search page at 60 results.

## `property_inputs` (type: `array`):

Auto-detects each entry and calls the right endpoint:
• Listing id (e.g. `EVPssE5S3KHLKudeJdhwT4`) → `/details/byid`
• `https://www.99.co/...` listing URL → `/details/byurl`

Each row = one full property record (price, address, agent contact, photos) enriched with similar listings, nearby amenities, floor plans, and project analysis (all in the `Raw` column).

## `enrich` (type: `boolean`):

When on, each property detail also includes `similarListings`, `nearbyAmenities`, `floorPlans`, and `projectAnalysis` blocks (kept in the `Raw` column). Turn off for a leaner, faster detail call.

## `agent_search_queries` (type: `array`):

Keyword matching agent or agency name → `/agent/search` (one row per agent, includes phone + slug). Use `*` to browse the full directory without a keyword. `Pages per search` and `Results per page` above apply.

## `agent_inputs` (type: `array`):

Full agent profile → `/agent/details`. Accepts the agent slug from `/agent/search` (e.g. `R046036F-jack-tan`) or a profile URL (`https://www.99.co/singapore/agents/...`). Returns contact info, agency, and listings breakdown.

## `autocomplete_inputs` (type: `array`):

Free-text location lookup → `/autocomplete`. One row per suggestion (MRT stations, districts, projects, schools) with its 99.co location id, type, and coordinates — useful for building precise searches.

## Actor input object example

```json
{
  "search_inputs": [
    "Orchard"
  ],
  "searchType": "For_Sale",
  "propertySegment": "residential",
  "propertyType": "all",
  "priceRange": "",
  "bedrooms": "",
  "bathrooms": "",
  "floorAreaRange": "",
  "moreFilters": "",
  "pages": 1,
  "resultCount": 25,
  "property_inputs": [
    "EVPssE5S3KHLKudeJdhwT4"
  ],
  "enrich": true,
  "agent_search_queries": [
    "tan"
  ],
  "agent_inputs": [],
  "autocomplete_inputs": []
}
```

# 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 = {
    "search_inputs": [
        "Orchard"
    ],
    "property_inputs": [
        "EVPssE5S3KHLKudeJdhwT4"
    ],
    "agent_search_queries": [
        "tan"
    ],
    "agent_inputs": [],
    "autocomplete_inputs": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("one-api/99co-scraper").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 = {
    "search_inputs": ["Orchard"],
    "property_inputs": ["EVPssE5S3KHLKudeJdhwT4"],
    "agent_search_queries": ["tan"],
    "agent_inputs": [],
    "autocomplete_inputs": [],
}

# Run the Actor and wait for it to finish
run = client.actor("one-api/99co-scraper").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 '{
  "search_inputs": [
    "Orchard"
  ],
  "property_inputs": [
    "EVPssE5S3KHLKudeJdhwT4"
  ],
  "agent_search_queries": [
    "tan"
  ],
  "agent_inputs": [],
  "autocomplete_inputs": []
}' |
apify call one-api/99co-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,one-api/99co-scraper"
        }
    }
}

```

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/GZIeatkoOW8jFO0TS/builds/3hx87lVGQg24aLm9f/openapi.json