All tools

Keyword Extractor

AI / Agent

Extract top keywords and phrases from text using TF-IDF scoring: useful for tagging, indexing, and RAG metadata.

Tagging a document for search or RAG metadata usually starts with figuring out what it's actually about, and this scores both single words and short n-gram phrases by TF-IDF relevance so you get candidate tags, including multi-word terms like "machine learning" scored as a unit rather than split apart. It's a statistical, frequency-based method rather than anything that understands meaning, so it surfaces distinctive terms well but can miss conceptually important words that simply don't repeat often, and it needs a reasonable amount of text to establish meaningful contrast: a single short sentence gives less reliable results than a full paragraph. Running it over several documents individually is a fast way to compare their dominant topics before deciding how to categorize them, all without anything leaving your browser.

keywordsextracttfidfnlpragtagsphrases

How to use Keyword Extractor

  • 1.Paste an article or document to get its top keywords and phrases ranked by TF-IDF relevance, useful for quick tagging.
  • 2.Use the extracted keywords as candidate metadata tags when indexing documents for a search or RAG system.
  • 3.Run it over several documents individually to compare their dominant topics at a glance before deciding how to categorize them.

Frequently asked questions

Does this run in my browser or on a server?
Extraction runs entirely client-side using TF-IDF scoring against the input text — nothing is uploaded.
Does it understand context or meaning, like an LLM would?
No — TF-IDF is a statistical, frequency-based method. It surfaces distinctive terms but doesn't understand semantics, so it can miss conceptually important words that don't repeat often.
Does it work well on very short text?
TF-IDF needs enough text to establish meaningful term frequency contrast — on a single short sentence, results are less reliable than on a full paragraph or document.
Can I extract multi-word phrases, not just single words?
Yes, it scores n-grams (short phrases) in addition to single keywords, which is useful for capturing terms like "machine learning" as a unit.

Use via API, SDK, or MCP

cURL# Free: 1,000 req/day · Pro: 10,000 req/day
curl -X POST https://api.utilix.tech/v1/tools/extract-keywords \
  -H "Authorization: Bearer utx_live_..." \
  -H "Content-Type: application/json" \
  -d '{"text": "Machine learning models require large datasets for training.", "maxKeywords": 5}'

Get an API key from your dashboard · Full API docs →

Related tools

Relevance ScoreScore a single text passage against a query. Returns a 0-1 relevance score, grade, matched terms, and coverage.AI / AgentRerank ChunksScore and rerank text chunks by relevance to a query using TF-IDF. Drop irrelevant chunks before LLM context.AI / AgentChunk TextSplit documents into overlapping chunks for RAG pipelines: by sentence, paragraph, or fixed size with configurable overlap.AI / Agent