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Connect String Similarity Batch 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. Offload heavy text comparison math to your agent.

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 · 2 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-02

2 capabilities in this set.

Part of 2 available through String Similarity Batch.

  1. 01

    Compute single metric

    This capability calculates a specific similarity metric, such as Levenshtein, between two individual strings.

  2. 02

    Batch rank candidates

    This capability ranks an entire array of strings based on their similarity to a target using metrics like Jaro-Winkler or Sorensen-Dice.

Real work

What teams actually run

01

Deduplication

Your agent identifies duplicate entries in a database by comparing string similarity.

02

Fuzzy Search

The agent ranks search results based on how closely they match a user's query.

03

Data Cleaning

You use the MCP to find typos or variations in large text datasets.

04

Record Linkage

The agent matches records across different datasets using similarity metrics.

One connector, every AI

String Similarity Batch 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 String Similarity Batch 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

699ms average. Fast in production.

String Similarity Batch is checked daily against the live service.

Daily averagePeak 812ms
Oct 3Today
Fastest day
554ms
Slowest day
812ms
14-day trend
Slowing+30%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 2 capabilities arrive 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 String Similarity Batch, so you can see the experience inside your AI.

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

String Similarity Batch Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_2bdBBIz3zwAoWQWPkFs0dCarqz9V041FolEup60x/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 — String Similarity Batch capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "string-similarity-batch-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_2bdBBIz3zwAoWQWPkFs0dCarqz9V041FolEup60x/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 String Similarity Batch in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work String Similarity Batch owners hand off.

Data professionals and developers who need to automate text matching without writing custom Python scripts.

  • 01

    Data Scientists

    They hand off fuzzy matching tasks to the agent to clean datasets.

  • 02

    Software Engineers

    They use the MCP to add string comparison logic to their existing AI workflows.

  • 03

    NLP Researchers

    They use these metrics to validate text similarity results.

FAQ

Questions String Similarity Batch owners ask.

  • 01

    What algorithms does this MCP support?

    It supports Levenshtein, Jaro-Winkler, Sorensen-Dice, Damerau-Levenshtein, and Longest Common Subsequence (LCS).

  • 02

    How long can the input strings be?

    The MCP handles strings up to 5000 characters in length.

  • 03

    Can I compare a single pair of words?

    Yes, you can use the compute_single_metric capability for one-to-one comparisons.

  • 04

    How do I use this in Claude or Cursor?

    You connect to the Vinkius-hosted MCP once, and the capabilities become available to your client automatically.

  • 05

    Why use this instead of just asking the AI?

    LLMs are not calculators. Using this MCP provides exact mathematical results rather than the AI's best guess.

  • 06

    Can I use this for large datasets?

    Yes, the batch_rank_canditates capability is designed to process arrays of candidates efficiently.

  • 07

    What is the maximum string length?

    Each individual string can be up to 5000 characters.

  • 08

    Does it support Jaro-Winkler?

    Yes, jaro_winkler is one of the supported metric types.

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