text-summarizer-extractor Connector for AI agents.
3 live capabilities
Extract exact keywords and extractive summaries from large documents for accurate data analysis.
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Why people use text-summarizer-extractor
Deterministic Text Summarizer & Extractor for Accurate Legal and Technical Data Extraction
This Connector cuts out the middleman. It uses math to rank sentences and pull out the most important ones. You get a summary that consists of actual quotes from your document, making it much easier to verify and much harder for the AI to mess up.
What Vinkius changes
You get mathematically accurate text extraction without any AI-generated fluff or hallucinations.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Extracting legal clauses
A lawyer asks their agent to find key clauses in a 50-page contract.
- Real-world use case 02
SEO topic modeling
An SEO lead wants to know the main themes of a competitor's transcript.
- Real-world use case 03
High-volume keyword counting
A content manager needs to know the top 20 topics in a library of blog posts.
Complete set · 3capabilities
The complete text-summarizer-extractor capability set.
These are the exact actions your AI can choose when you ask it to work with text-summarizer-extractor.
01—03
3 capabilities in this set.
Part of 3 available through text-summarizer-extractor.
- 01 Capability
Extract top bigrams
Extracts the top N most frequent two-word phrases from a text. It is perfect for identifying recurring themes or finding SEO trends.
- 02 Capability
Extract top keywords
Extracts the top N most frequent keywords from a text using a Term Frequency algorithm. It automatically ignores common stop words like the or and.
- 03 Capability
Extractive summary
Performs algorithmic extractive summarization on a source text. It selects the most mathematically relevant sentences to ensure the summary contains only original content.
Set up in minutes
One URL. Then ask text-summarizer-extractor to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use text-summarizer-extractor from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_x32zMiM6lRsYu5lv1NDLGVRYYFMM8douF0KY03eU/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it text-summarizer-extractor, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable text-summarizer-extractor for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_x32zMiM6lRsYu5lv1NDLGVRYYFMM8douF0KY03eU/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the text-summarizer-extractor URL.
- Step 03
Save and start
Save the connection and enable text-summarizer-extractor in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-text-summarizer-extractor": {
"url": "https://edge.vinkius.com/vk_preview_x32zMiM6lRsYu5lv1NDLGVRYYFMM8douF0KY03eU/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using text-summarizer-extractor
Open Agent mode in chat and ask: "Using text-summarizer-extractor, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-text-summarizer-extractor": {
"url": "https://edge.vinkius.com/vk_preview_x32zMiM6lRsYu5lv1NDLGVRYYFMM8douF0KY03eU/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using text-summarizer-extractor
Ask Copilot: "Using text-summarizer-extractor, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-text-summarizer-extractor": {
"url": "https://edge.vinkius.com/vk_preview_x32zMiM6lRsYu5lv1NDLGVRYYFMM8douF0KY03eU/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using text-summarizer-extractor
Open Cascade and ask: "Using text-summarizer-extractor, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-text-summarizer-extractor": {
"url": "https://edge.vinkius.com/vk_preview_x32zMiM6lRsYu5lv1NDLGVRYYFMM8douF0KY03eU/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using text-summarizer-extractor
Ask Cline: "Using text-summarizer-extractor, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add deterministic-text-summarizer-extractor --transport http "https://edge.vinkius.com/vk_preview_x32zMiM6lRsYu5lv1NDLGVRYYFMM8douF0KY03eU/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using text-summarizer-extractor
Ask Claude: "Using text-summarizer-extractor, show me...". 3 tools are ready
Where the request belongs
Work text-summarizer-extractor can move forward.
This is for researchers and data specialists who can't afford for an AI to rephrase their data. If you need to know exactly what a document says without the risk of a hallucination, this is your capability.
SEO Specialist
Analyzing transcripts to find high-frequency phrases for content strategy on a Tuesday afternoon.
Legal Researcher
Extracting key clauses from long contracts where exact wording is mandatory for compliance.
Data Analyst
Cleaning up large text datasets to identify core topics quickly without manual sorting.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Analyze text and media with OneAI Language Skills—summarize, extract entities, and transcribe audio directly through your AI agent.
MonkeyLearn
Analyze text data with custom machine learning models that classify sentiment, extract keywords, and tag topics automatically.
Keyword Extractor
Extract and rank significant keywords from text using term frequency and density analysis.
TextRazor
Advanced Natural Language Processing (NLP) to extract entities, topics, and relations from text or URLs.
Bring your own AI
Change the model, client or framework. Keep text-summarizer-extractor connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
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Amazon Q -
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Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about text-summarizer-extractor.
The practical details behind the request, access and result.
Can the Deterministic Text Summarizer & Extractor handle different languages?
Yes, it supports English, Portuguese, and Spanish stop words for keyword extraction.
Will the Deterministic Text Summarizer & Extractor change my original text?
No, it only pulls out existing sentences from your source text to ensure 100% accuracy.
How is this different from a normal AI summary?
A normal summary rewrites the text, while this Connector uses math to extract the original sentences that are most relevant.
Can I use the Deterministic Text Summarizer & Extractor for SEO?
Yes, it's great for identifying recurring bigrams and frequent keywords in any content.
Is the Deterministic Text Summarizer & Extractor fast?
Yes, it runs on a pure Javascript runtime, making it extremely fast for processing large amounts of text.
Does the Deterministic Text Summarizer & Extractor need an API key?
No, it runs locally on your machine or within your AI client's environment.
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 capability 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 capability 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.
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