Vinkius
Deterministic Text Summarizer

Supercharge your AI with Deterministic Text Summarizer. Extract facts, not AI guesses.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
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Works with every AI agent you already use

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Connect to your AI in seconds.

The Deterministic Text Summarizer & Extractor MCP provides pure, mathematical text analysis without needing external API calls or hallucination risk.

It extracts key information by pulling exact sentences and phrases directly from source material using Term Frequency (TF) algorithms. Use this to reliably find core concepts, analyze keyword density, and condense long documents into actionable data points.

What your AI can do

Extract top bigrams

Pulls the top N most common two-word phrases from a text, ideal for mapping out SEO topics or semantic links.

Extract top keywords

Calculates and returns the top N keywords based on term frequency, filtering out meaningless stop words.

Extractive summary

Runs a mathematical algorithm to select and combine the most important sentences from a document for condensation.

Generate factual summaries

Selects the most mathematically important sentences from a document and compiles them into an extractive summary.

Identify core concepts by frequency

Counts the top recurring keywords in a text using Term Frequency analysis, ignoring common stop words like 'the' or 'a'.

Model topical relationships

Finds and counts the most frequently occurring two-word phrases (bigrams), useful for understanding semantic connections.

Compatible AI Apps

OAuth 2.0 Compatible
Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
Vinkius runs on Zendesk Zendesk
+ any other MCP app
Included with Plan

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AI Agent

Deterministic Text Summarizer & Extractor: 3 Tools

These three tools allow you to process text by extracting keyword counts, identifying common two-word phrases, or creating mathematically supported summaries.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Deterministic Text Summarizer & Extractor on Vinkius

Extract Top Bigrams

Pulls the top N most common two-word phrases from a text, ideal for mapping out SEO topics or semantic links.

Extract Top Keywords

Calculates and returns the top N keywords based on term frequency, filtering out...

Extractive Summary

Runs a mathematical algorithm to select and combine the most important sentences...

Connect to your AI in seconds. Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Deterministic Text Summarizer integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
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  • Deploy to edge with MCPFusion framework
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Start building

Make Your AI Do More

Start with Deterministic Text Summarizer & Extractor, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,000+ others, all in one place
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  • Every connection is secured and compliant automatically
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  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog every week
Deterministic Text Summarizer MCP server cover

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 3 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Analyzing large texts usually means copy-pasting into a chat window.

Right now, when you get a massive PDF or research paper, your workflow is manual. You open the file, skim the introduction, highlight key paragraphs, and then spend time copying those chunks of text into a separate document just to keep track of what was important. It's tedious, slow, and easy to lose context in the copy/paste process.

With this MCP, you simply feed the full document to your agent. You instruct it to analyze the structure mathematically, whether that’s using `extract_top_keywords` or running an extractive summary. What changes is that you get a clean, structured output—a list of facts and phrases—without having to manage any manual copy-pasting.

Extracting core concepts with the Deterministic Text Summarizer & Extractor MCP

Before this, identifying key themes meant relying on a general LLM prompt and hoping it didn't miss anything critical or hallucinate. You were guessing at importance. The manual step was always verifying that the generated summary actually contained verifiable proof in the original text.

Now you can run `extract_top_bigrams` to see exactly which two-word phrases dominate the discourse, or use `extractive_summary` to get a mathematically defined set of core sentences. You know the output is clean and directly traceable.

What your AI can actually do with this

When you need to extract facts, not interpretations, this MCP is the right tool. Most large language models generate 'abstractive' summaries; they write new text based on what they think the source means. That process is prone to hallucination and burns through tokens fast. Our approach flips that script entirely.

It uses pure math—Term Frequency analysis—to identify the most statistically important parts of a document, pulling out those exact, unmodified sentences. This MCP lets you analyze text structure directly. Need to find recurring themes or boost SEO content? You can use it to pinpoint the top two-word phrases (bigrams) or count core vocabulary with extract_top_keywords.

By connecting this through Vinkius, your agent gets a guaranteed way to process complex documents for strict data extraction.

Built · Hosted · Managed by Vinkius Text Summarizer & Extractor MCP - Analyze Text Structure
Server ID 019e38f9-f5e2-73c1-9811-38e4f31c3b72
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Questions you might have

What is the difference between Extractive and Abstractive summarization? +

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.

Does the keyword extraction ignore simple connection words? +

Yes. It has a built-in cross-language 'Stop Words' dictionary (supporting English, Portuguese, and Spanish) to ensure words like 'the', 'and', 'for', 'uma' are completely ignored during Term Frequency calculations.

Why use this tool instead of just asking an AI to summarize? +

If you have a massive 50-page document, passing the entire text into an AI context window is extremely expensive and slow. Running an algorithmic extraction first condenses the text dramatically while retaining all key facts.

Do I need to connect any external API keys for `extractive_summary` to work? +

No, you don't. This MCP uses a purely mathematical algorithm that runs in the Javascript runtime. It never requires connecting to paid APIs or external services.

What determines the performance of the Deterministic Text Summarizer & Extractor? +

It’s fast because it's built on a pure JS runtime. The system analyzes text frequency directly, avoiding resource-intensive calls that bog down traditional NLP packages.

How does using `extract_top_bigrams` differ from running `extract_top_keywords`? +

Keywords find single words based on their individual frequency. Bigrams, however, look for pairs of adjacent words that appear together often, giving you a deeper semantic view.

Does the Deterministic Text Summarizer & Extractor have limits when running `extract_top_keywords`? +

The tool is designed to handle large volumes of text efficiently. It processes data by calculating term frequency, which scales better than model-based approaches.

Is the Deterministic Text Summarizer & Extractor suitable for non-English content using `extractive_summary`? +

While optimized for English stop word handling, it uses a foundational Term Frequency (TF) algorithm. You can run it on other languages to extract important phrases.

Built & Managed by Vinkius 30s setup 3 tools

We've already built the connector for Deterministic Text Summarizer. Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 3 tools are live and waiting. You're up and running in seconds.

Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on Windsurf Windsurf
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
+ other MCP clients

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