Deterministic Text Summarizer & Extractor

Deterministic Text Summarizer & Extractor MCP Connector for Claude

A+

Equip your AI with pure Term Frequency (TF) text analysis. Deterministically extract keywords, bigrams, and generate extractive summaries without external API calls.

3 tools Official Updated Jun 28, 2026 Official Vinkius Partner

Large Language Models generate 'Abstractive' summaries (they write new text based on their understanding), which consumes a massive amount of tokens and can introduce hallucinations or skip crucial facts. The Text Summarizer & Extractor MCP solves this by using 'Extractive' summarization—a purely mathematical algorithm (Term Frequency) that pulls the exact, unmodified, most important sentences directly from the source text. It is the ultimate pre-processing tool for strict data extraction.

The Superpowers

  • Extractive Summarization: Ranks all sentences in a document mathematically by keyword density and extracts the top N sentences. Zero hallucination.
  • Keyword Extraction: Instantly counts term frequency (TF) to find the most repeated topics, completely ignoring grammatical stop words (English, Portuguese, Spanish).
  • Bigram Analysis: Finds the most common two-word phrases, perfect for SEO topic modeling and strict semantic analysis.
  • Zero-Dependency Architecture: Pure Javascript runtime execution guarantees absolute speed without bloated NLP packages.
extractive-summarizationterm-frequencykeyword-extractiontext-analysisnlp

3 tools expose this connector's capabilities to your AI agent.

extract_top_bigrams

Extracts the top N most frequent two-word phrases (bigrams). Excellent for SEO topic modeling

extract_top_keywords

Extracts the top N most frequent keywords from a text (TF algorithm), ignoring stop words

extractive_summary

Performs algorithmic extractive summarization. It selects the most mathematically important sentences based on Term Frequency (TF)

See how to talk to your AI agent using Deterministic Text Summarizer & Extractor.

Create a 3-sentence extractive summary of this long article.

Using the extractive_summary tool (sentenceCount=3): Here are the 3 most mathematically relevant sentences extracted exactly from the source.

What are the top 10 keywords in this SEO text?

Using the extract_top_keywords tool (topN=10): The JSON array shows the top frequency counts, ignoring standard stop words.

Find the top 5 bigrams (two-word phrases) repeated in this transcript.

Using the extract_top_bigrams tool: The most repeated bigram is 'machine learning' with 14 occurrences.

Abstractive summarization (what ChatGPT does) writes a completely new text based on its understanding. Extractive summarization (what this tool does) selects the most mathematically important sentences directly from the original text without changing a single word. It guarantees 100% factual accuracy.

Related Connectors