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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Unicode Normalization and Homoglyph Detector with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Detects malicious Unicode homoglyph attacks and identifies invisible characters in strings.

Included with plan

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

Complete set · 3 capabilities

The complete Unicode Normalization and Homoglyph Detector capability set.

These are the exact actions your AI can choose when you ask it to work with Unicode Normalization and Homoglyph Detector.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Unicode Normalization and Homoglyph Detector.

  1. 01

    Analyze string security

    Provides a high-level security assessment of a provided string

  2. 02

    Inspect homoglyph substitutions

    Isolates and reports only the visual substitutions found in a string

  3. 03

    Detect hidden characters

    Scans for the presence of invisible or zero-width characters

Observed, not estimated

640ms average. Fast in production.

Unicode Normalization and Homoglyph Detector is checked daily against the live service.

Daily averagePeak 769ms
Aug 20Today
Fastest day
472ms
Slowest day
769ms
14-day trend
Slowing+28%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 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 Unicode Normalization and Homoglyph Detector, so you can see the experience inside your AI.

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

Unicode Normalization and Homoglyph Detector Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_brw1ch91jN7AcuEA8uccnvyhh8FVpllEmkNqeVKz/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 — Unicode Normalization and Homoglyph Detector capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "unicode-normalization-and-homoglyph-detector-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_brw1ch91jN7AcuEA8uccnvyhh8FVpllEmkNqeVKz/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

FAQ

Questions Unicode Normalization and Homoglyph Detector owners ask.

  • 01

    What are homoglyph attacks?

    Homoglyph attacks occur when visually similar characters from different scripts (like Cyrillic or Greek) are used to impersonate Latin characters, potentially creating deceptive URLs or usernames.

  • 02

    How does the capability detect hidden characters?

    The detect_hidden_characters capability scans for specific Unicode codepoints that have no visual width, such as U+200B (Zero Width Space), which are often used to hide malicious payloads.

  • 03

    Can I normalize strings using this server?

    Yes, when using analyze_string_security, you can set the applyNormalization parameter to true to receive the string in its standardized NFC (Normalization Form Canonical Composition) format.

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