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Connect Tf Idf Vectorizer Engine to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Replace LLM keyword guessing with deterministic statistical scores.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 1 capability

We ship only the actions that matter.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through natural.

  1. 01

    Calculate tf idf

    This capability calculates exact TF-IDF scores for specific terms across a provided set of documents. It provides the mathematical foundation for ranking document relevance.

Real work

What teams actually run

01

Technical Support Analysis

An agent analyzes hundreds of support tickets to find which ones specifically mention a new software bug.

02

Content Relevance Ranking

A user ranks a collection of news articles based on how heavily they discuss specific economic terms.

03

Customer Feedback Filtering

An agent processes customer reviews to isolate feedback regarding specific product features.

04

Corpus Summarization

A developer uses the scores to identify the most defining terms in a massive dataset of documents.

Automate a task

Put natural to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

natural works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put natural to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

859ms average. Fast in production.

natural is checked daily against the live service.

Daily averagePeak 1021ms
Oct 3Today
Fastest day
674ms
Slowest day
1021ms
14-day trend
Improving-14%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 1 capability arrives ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of natural, so you can see the experience inside your AI.

It does not authenticate your account with natural. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

natural Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_CzteX5B7baA5kKcgQISGvHapYHeKBksKMIECPMUI/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — natural capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "tf-idf-vectorizer-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_CzteX5B7baA5kKcgQISGvHapYHeKBksKMIECPMUI/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up natural in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work natural owners hand off.

This MCP is built for technical users who need to bridge the gap between natural language and statistical data.

  • 01

    Data Scientists

    They hand off large text arrays to the agent to get precise statistical weights for NLP pipelines.

  • 02

    NLP Engineers

    They use the engine to validate keyword importance without relying on LLM intuition.

  • 03

    Software Developers

    They integrate deterministic text scoring into agentic workflows for better search and retrieval.

FAQ

Questions natural owners ask.

  • 01

    How is this different from asking an LLM to find keywords?

    LLMs guess based on probability, which leads to hallucinations. This MCP uses deterministic math to provide exact scores.

  • 02

    Which AI clients can use this MCP?

    You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 03

    What engine performs the calculations?

    The calculations are performed locally using the Node.js V8 engine for mathematical precision.

  • 04

    Do I need to host this myself?

    No, Vinkius hosts and manages the MCP for you. You just connect your client and start using the capabilities.

  • 05

    Can I use this for real-time text analysis?

    Yes, the engine is designed to handle arrays of documents and terms for immediate scoring.

  • 06

    Why is TF-IDF better than simple word counting?

    Word counting overvalues common words like 'the' or 'and'. TF-IDF lowers the weight of words that appear in many documents, highlighting terms that are uniquely relevant to a specific text.

  • 07

    Can it process JSON document arrays?

    Yes, just provide a stringified JSON array of text documents and a target array of terms. The engine handles the corpus building and tokenization.

  • 08

    Does it work in languages other than English?

    Yes, TF-IDF relies on token frequency, making it highly effective for multi-language corpuses without needing specific translation logic.

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