# Text Analysis - Sentiment, Keywords, NLP (`lazymac/text-analysis-toolkit`) Actor

🔥 7-DAY LAUNCH SPRINT (May 1–8, 2026): First 100 runs free for new users. Natural Language Processing toolkit. Perform sentiment analysis, keyword extraction, readability scoring, language detection, and text summarization. Ideal for content analysis, social media monitoring, and text mining.

- **URL**: https://apify.com/lazymac/text-analysis-toolkit.md
- **Developed by:** [2x lazymac](https://apify.com/lazymac) (community)
- **Categories:** AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

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/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.

- **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

## Text Analysis Toolkit

Analyze text for sentiment, readability, keywords, language, stats, profanity, and generate summaries.

### Input

- `text` (string, required): Text to analyze
- `analyses` (array): Which analyses to run — `all`, `sentiment`, `readability`, `keywords`, `language`, `stats`, `profanity`, `summarize`
- `maxKeywords` (integer): Maximum keywords to extract (default 10)
- `summaryLength` (integer): Number of sentences in summary (default 3)

### Output

Returns analysis results including sentiment scores, readability metrics, keywords, language detection, text stats, profanity check, and summary.

# Actor input Schema

## `text` (type: `string`):

Text to analyze

## `analyses` (type: `array`):

Which analyses to run: all, sentiment, readability, keywords, language, stats, profanity, summarize

## `maxKeywords` (type: `integer`):

Maximum number of keywords to extract

## `summaryLength` (type: `integer`):

Number of sentences in summary

## Actor input object example

```json
{
  "text": "The quick brown fox jumps over the lazy dog. Artificial intelligence is transforming how we work and live. This sample text demonstrates natural language processing capabilities.",
  "analyses": [
    "all"
  ],
  "maxKeywords": 10,
  "summaryLength": 3
}
```

# 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 = {
    "text": "The quick brown fox jumps over the lazy dog. Artificial intelligence is transforming how we work and live. This sample text demonstrates natural language processing capabilities."
};

// Run the Actor and wait for it to finish
const run = await client.actor("lazymac/text-analysis-toolkit").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 = { "text": "The quick brown fox jumps over the lazy dog. Artificial intelligence is transforming how we work and live. This sample text demonstrates natural language processing capabilities." }

# Run the Actor and wait for it to finish
run = client.actor("lazymac/text-analysis-toolkit").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 '{
  "text": "The quick brown fox jumps over the lazy dog. Artificial intelligence is transforming how we work and live. This sample text demonstrates natural language processing capabilities."
}' |
apify call lazymac/text-analysis-toolkit --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=lazymac/text-analysis-toolkit",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/BAewpq6uBn0BD9r0d/builds/Y0xzUtckLWPmrobJG/openapi.json