# Multi Topic Quotes API (`b2b_lead_generation/multi-topic-quotes-api`) Actor
Multi-Topic Quotes API returns clean quote records by topic in one click. Pick from a wide topic dropdown and get structured rows with the quote, author, and tags, ready for Sheets, Airtable, or Notion.
- **URL**: https://apify.com/b2b\_lead\_generation/multi-topic-quotes-api.md
- **Developed by:** [B2B Lead Generation](https://apify.com/b2b_lead_generation) (community)
- **Categories:** Developer tools, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $1.99 / 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/platform/actors/running/actors-in-store#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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).
If your project is in a different language, use 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
## Multi-Topic Quotes API: Get Quotes by Topic in One Click
Multi-Topic Quotes API is the simplest way to pull clean, structured quote records for the topics you care about. Pick one or more topics from the built-in dropdown, set how many quotes you want, and the actor delivers a ready-to-use dataset with the quote text, the author, and its tags. No API keys, no third-party accounts, no cleanup work. It is built for content teams, indie developers, and researchers who want quotes without turning it into a data engineering project.
### What this actor does
Multi-Topic Quotes API accepts a list of topics (chosen from a curated dropdown) and returns matching quote records up to the limit you set. Selecting several topics widens the search: a record is returned if it belongs to any of the topics you picked. There is nothing else to configure, no filters to tune, no scoring to interpret. Pick topics, run, done.
Because the topic list is a controlled dropdown, you cannot fat-finger a filter. Every option in the list is guaranteed to return real results, and the matching is deterministic: a topic either matches or it does not.
### Use cases
- **Content writing**: pull a batch of quotes on business, leadership, or productivity for a blog post round-up in one click
- **Social media scheduling**: pick topics like motivational, humor, or morning and feed a whole week of quote graphics into a scheduling tool
- **Newsletter curation**: choose topics that fit your audience for a themed Monday send, ready to paste into your ESP
- **App and product development**: seed a quote database for a mobile, web, or Slack app without stitching sources together by hand
- **Research and academic writing**: gather quotes on a specific concept, such as death, faith, or courage, for a literature review
- **Chatbot and LLM training**: feed clean topic-labeled quote records into a fine-tuning dataset or a retrieval-augmented generation pipeline
- **Educational content**: build worksheets, flashcards, or lesson materials with attributed quotes on a chosen theme
- **Greeting card and gift copy**: pull quotes tagged with anniversary, birthday, wedding, or thanksgiving for occasion-specific messaging
### Input
The actor has a tiny, focused input schema. Two fields. Nothing to configure beyond your topics and the item cap.
| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `topics` | array (dropdown, multi-select) | none | Pick one or more topics from the built-in dropdown. The actor returns quotes filed under any of the selected topics. **Required.** |
| `maxItems` | integer | `100` | Cap on returned quotes. Hard maximum: 100000. |
Available topics in the dropdown include age, art, business, courage, dreams, education, family, faith, freedom, friendship, funny, happiness, health, hope, inspiration, leadership, life, love, marriage, morning, motivational, nature, peace, positivity, power, relationship, religion, respect, romantic, sad, science, smile, society, sports, strength, success, teacher, technology, time, travel, trust, truth, war, wedding, wisdom, women, work, and many more, including occasion-specific topics like anniversary, birthday, christmas, easter, fathers-day, mothers-day, memorial-day, new-years, saint-patricks-day, thanksgiving, valentines-day, and veterans-day.
#### Example input: quotes on one topic
```json
{
"topics": ["business"],
"maxItems": 50
}
````
#### Example input: quotes across several related topics
```json
{
"topics": ["motivational", "inspirational", "success"],
"maxItems": 200
}
```
#### Example input: occasion-specific messaging
```json
{
"topics": ["christmas", "thanksgiving", "new-years"],
"maxItems": 100
}
```
### What data does this actor return?
The actor pushes every matched quote into the run's dataset. Each record looks like this:
```json
{
"topic": "business",
"quoteTitle": "The way to get started is to quit talking and begin doing.",
"author": "Walt Disney",
"quoteTags": "Way, Talking, Doing"
}
```
| Field | Type | Description |
|-------|------|-------------|
| `topic` | string | Topic category the quote is filed under. |
| `quoteTitle` | string | The quote text itself. |
| `author` | string | Author of the quote. |
| `quoteTags` | string | Comma-separated tags describing the quote. |
Export the dataset directly from the Apify console as JSON, XML, or Excel, or pipe it into an integration. Every record is self-contained, so downstream tools can index it right away.
### How it works
1. The actor reads your selected topics and item cap from the run configuration.
2. Topic values are normalized (case-folded) so casing mismatches never cause a miss.
3. The actor queries the quotes service for records matching any of the selected topics.
4. Matched records are pushed to the dataset until `maxItems` is reached.
5. The run finishes and results are ready for export or integration.
### Tips for getting the most out of it
- **Pick related topics together**. Selecting motivational, inspirational, and success at once is faster than three separate runs and gives you a broader pool for the same audience.
- **Set `maxItems` deliberately**. The default of 100 keeps runs snappy and cheap. Bump it only when you actually need more.
- **Chain runs into integrations**. Push the dataset straight to Google Sheets, Airtable, or Notion for a live-updating content library.
- **Schedule occasion-specific runs**. Set a monthly schedule to fetch fresh quotes for the next holiday, so your content pipeline is always ready.
### FAQ
**Do I need an API key, account, or third-party subscription?**
No. The actor is self-contained. Pick topics and it runs.
**Can I mix any topics I want?**
Yes. The dropdown is multi-select. A record is returned if its topic matches any of the topics you picked (OR logic across topics).
**What happens if I select nothing?**
The run stops with a clear message asking you to pick at least one topic. This is intentional so you never accidentally pull a huge unfiltered dataset.
**Is the output usable directly in Google Sheets, Notion, or Airtable?**
Yes. Export the dataset as CSV or JSON from the Apify console, or connect the built-in Google Sheets, Airtable, or Notion integrations to auto-deliver results.
**Can I run this on a schedule?**
Yes. Use Apify's built-in schedules to run daily, weekly, or on any cron expression. Pair it with a webhook or an integration to auto-deliver fresh quotes to Slack, email, or a spreadsheet.
**How fast is a run?**
Typical runs finish in seconds. Even large `maxItems` values complete in under a minute. There is no browser, no headless rendering, and no external API round-trip.
**What is a "quote record"?**
A single object containing the topic, the quote text, the author, and its tags. Every record is standalone, so you can drop it directly into a database, a CMS, or a content template.
**Can I get the same author across different topics?**
Yes. Pick the topics you want and the actor returns quotes for all of them. Authors are attached to each record, so you can group or filter downstream.
### Integrations and automations
Connect Multi-Topic Quotes API with other apps and services using [Apify integrations](https://apify.com/integrations). Send matched quotes to Google Sheets, Airtable, Notion, Slack, or your own [webhook](https://docs.apify.com/integrations/webhooks) after every run. It plays nicely with Make, Zapier, Airbyte, GitHub, and Google Drive. Pair it with an Apify schedule and you have a self-updating content pipeline that never asks for your attention until you want a new query.
### Performance and cost
Runs are fast and cheap. The actor uses a single lightweight dependency and no browser, so memory and CPU cost stay low. That makes it a good candidate for high-frequency scheduled runs on a small compute plan. A typical topic query with `maxItems: 100` finishes in seconds.
### Support and feedback
Found a topic that behaves oddly, or want a new integration hook? Open an issue on the actor's Apify page. Feature requests, topic suggestions, and integration ideas are all welcome.
***
Multi-Topic Quotes API turns a broad quotes lookup into a one-click, topic-driven feed for content workflows, research, and app data. No scraping, no cleanup, no fluff.
# Actor input Schema
## `topics` (type: `array`):
Pick one or more topics from the dropdown. The actor returns quotes filed under any of the selected topics.
## `maxItems` (type: `integer`):
Cap the number of matched quotes returned.
## Actor input object example
```json
{
"topics": [
"age"
],
"maxItems": 100
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"topics": [
"age"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("b2b_lead_generation/multi-topic-quotes-api").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "topics": ["age"] }
# Run the Actor and wait for it to finish
run = client.actor("b2b_lead_generation/multi-topic-quotes-api").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"topics": [
"age"
]
}' |
apify call b2b_lead_generation/multi-topic-quotes-api --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=b2b_lead_generation/multi-topic-quotes-api",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Multi Topic Quotes API",
"description": "Multi-Topic Quotes API returns clean quote records by topic in one click. Pick from a wide topic dropdown and get structured rows with the quote, author, and tags, ready for Sheets, Airtable, or Notion.",
"version": "0.0",
"x-build-id": "SecW2qeW6R02DrMRy"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/b2b_lead_generation~multi-topic-quotes-api/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-b2b_lead_generation-multi-topic-quotes-api",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/b2b_lead_generation~multi-topic-quotes-api/runs": {
"post": {
"operationId": "runs-sync-b2b_lead_generation-multi-topic-quotes-api",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/b2b_lead_generation~multi-topic-quotes-api/run-sync": {
"post": {
"operationId": "run-sync-b2b_lead_generation-multi-topic-quotes-api",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"topics"
],
"properties": {
"topics": {
"title": "Topics",
"uniqueItems": true,
"type": "array",
"description": "Pick one or more topics from the dropdown. The actor returns quotes filed under any of the selected topics.",
"items": {
"type": "string",
"enum": [
"age",
"alone",
"amazing",
"anger",
"anniversary",
"architecture",
"art",
"attitude",
"beauty",
"best",
"birthday",
"brainy",
"business",
"car",
"chance",
"change",
"christmas",
"communication",
"computers",
"cool",
"courage",
"dad",
"dating",
"death",
"design",
"diet",
"dreams",
"easter",
"education",
"environmental",
"equality",
"experience",
"failure",
"faith",
"family",
"famous",
"fathers-day",
"fear",
"finance",
"fitness",
"food",
"forgiveness",
"freedom",
"friendship",
"funny",
"future",
"gardening",
"god",
"good",
"government",
"graduation",
"great",
"happiness",
"health",
"history",
"home",
"hope",
"humor",
"imagination",
"independence",
"inspirational",
"intelligence",
"jealousy",
"knowledge",
"leadership",
"learning",
"legal",
"life",
"love",
"marriage",
"medical",
"memorial-day",
"men",
"mom",
"money",
"morning",
"mothers-day",
"motivational",
"movies",
"moving-on",
"music",
"nature",
"new-years",
"parenting",
"patience",
"patriotism",
"peace",
"pet",
"poetry",
"politics",
"positive",
"power",
"relationship",
"religion",
"respect",
"romantic",
"sad",
"saint-patricks-day",
"science",
"smile",
"society",
"space",
"sports",
"strength",
"success",
"sympathy",
"teacher",
"technology",
"teen",
"thankful",
"thanksgiving",
"time",
"travel",
"trust",
"truth",
"valentines-day",
"veterans-day",
"war",
"wedding",
"wisdom",
"women",
"work"
],
"enumTitles": [
"Age",
"Alone",
"Amazing",
"Anger",
"Anniversary",
"Architecture",
"Art",
"Attitude",
"Beauty",
"Best",
"Birthday",
"Brainy",
"Business",
"Car",
"Chance",
"Change",
"Christmas",
"Communication",
"Computers",
"Cool",
"Courage",
"Dad",
"Dating",
"Death",
"Design",
"Diet",
"Dreams",
"Easter",
"Education",
"Environmental",
"Equality",
"Experience",
"Failure",
"Faith",
"Family",
"Famous",
"Fathers Day",
"Fear",
"Finance",
"Fitness",
"Food",
"Forgiveness",
"Freedom",
"Friendship",
"Funny",
"Future",
"Gardening",
"God",
"Good",
"Government",
"Graduation",
"Great",
"Happiness",
"Health",
"History",
"Home",
"Hope",
"Humor",
"Imagination",
"Independence",
"Inspirational",
"Intelligence",
"Jealousy",
"Knowledge",
"Leadership",
"Learning",
"Legal",
"Life",
"Love",
"Marriage",
"Medical",
"Memorial Day",
"Men",
"Mom",
"Money",
"Morning",
"Mothers Day",
"Motivational",
"Movies",
"Moving On",
"Music",
"Nature",
"New Years",
"Parenting",
"Patience",
"Patriotism",
"Peace",
"Pet",
"Poetry",
"Politics",
"Positive",
"Power",
"Relationship",
"Religion",
"Respect",
"Romantic",
"Sad",
"Saint Patricks Day",
"Science",
"Smile",
"Society",
"Space",
"Sports",
"Strength",
"Success",
"Sympathy",
"Teacher",
"Technology",
"Teen",
"Thankful",
"Thanksgiving",
"Time",
"Travel",
"Trust",
"Truth",
"Valentines Day",
"Veterans Day",
"War",
"Wedding",
"Wisdom",
"Women",
"Work"
]
}
},
"maxItems": {
"title": "Max items",
"minimum": 1,
"maximum": 100000,
"type": "integer",
"description": "Cap the number of matched quotes returned.",
"default": 100
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```