An astronaut overseeing a futuristic data hub
Download PDFMarkdown Version

Connect Stemmer Lemmatizer 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. Reduce vocabulary size and prep text for vector databases.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

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

    Stem text corpus

    This capability applies Porter or Lancaster stemming algorithms to tokenize and stem your text. It's the primary way to reduce your corpus to its base linguistic forms.

Real work

What teams actually run

01

RAG Optimization

Clean your documents before embedding them to ensure better retrieval hits.

02

Topic Modeling

Reduce word variance to help clustering algorithms find clearer themes.

03

Search Engine Prep

Normalize user queries and document indexes to improve keyword matching.

04

Vocabulary Compression

Shrink the size of your unique word list to save space in vector databases.

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

928ms average. Fast in production.

natural is checked daily against the live service.

Daily averagePeak 1084ms
Oct 3Today
Fastest day
700ms
Slowest day
1084ms
14-day trend
Improving-8%

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_irXfMdMMaEZGVkqPil2LsPCgt9v0l0ULTfqQ1ZDs/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": {
    "stemmer-lemmatizer-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_irXfMdMMaEZGVkqPil2LsPCgt9v0l0ULTfqQ1ZDs/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.

Data engineers and AI developers building RAG pipelines or search engines.

  • 01

    NLP Engineer

    Hands off raw text corpora to the MCP to prepare them for embedding models.

  • 02

    Data Scientist

    Uses the engine to normalize text before performing topic modeling or clustering.

  • 03

    AI Developer

    Connects the MCP to their agent to reduce token costs during data preprocessing.

FAQ

Questions natural owners ask.

  • 01

    How is this different from asking an LLM to stem text?

    Using an LLM for stemming is slow and expensive. This MCP uses direct algorithms like Porter and Lancaster, which are faster, cheaper, and produce deterministic results without the risk of semantic hallucination.

  • 02

    Which algorithms are supported?

    This MCP supports both the Porter and Lancaster stemming algorithms.

  • 03

    What clients can I use this with?

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

  • 04

    Can I use this for RAG?

    Yes. It is specifically designed to help prepare text for vector search and RAG by normalizing words to their roots.

  • 05

    Do I need to host this myself?

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

  • 06

    Porter vs Lancaster?

    Porter is gentler and more common. Lancaster is aggressive and creates much shorter stems (sometimes stripping prefixes/suffixes completely).

  • 07

    Does it help with RAG?

    Yes! Stemming documents before embedding them reduces vector dimensionality and increases recall for different word variations.

  • 08

    Does it do tokenization?

    Yes, it automatically tokenizes the string, stems each word, and rejoins them for your convenience.

Explore

More in Developer Tools

Suggestions

Connect natural to Claude, Cursor, ChatGPT & more