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Connect Type Definition Consistency Checker to your AI

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. Stop structural drift between your frontend and backend schemas.

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 · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Type Definition Consistency Checker.

  1. 01

    Compare definitions

    This capability compares two specific type definitions to find differences. It's useful for reviewing a single change against an existing schema.

  2. 02

    Sync definitions

    This capability performs a full-suite audit across multiple definitions. Use it to ensure an entire set of schemas stays synchronized.

  3. 03

    Inspect structure

    This capability provides parsed metadata for a single type definition. It lets your AI client see the exact fields and types within a schema.

Real work

What teams actually run

01

Refactoring Schemas

Verify that a change to a backend Pydantic model hasn't broken the corresponding Zod schema on the frontend.

02

API Contract Validation

Ensure your TypeScript interfaces strictly follow the data structures defined in your backend models.

03

New Feature Integration

Check if a newly added field in a schema is correctly represented across all related type definitions.

04

Codebase Auditing

Run a full synchronization check to find any existing discrepancies in your type definitions.

One connector, every AI

Type Definition Consistency Checker 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 Type Definition Consistency Checker 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.

Type Definition Consistency Checker is checked daily against the live service.

Daily averagePeak 782ms
Oct 3Today
Fastest day
567ms
Slowest day
782ms
14-day trend
Improving-5%

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 Type Definition Consistency Checker, so you can see the experience inside your AI.

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

Type Definition Consistency Checker Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_e9qkPrv0oxwaJFM5IRMYH0SAdmGX3uUy7kc4Yxip/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 — Type Definition Consistency Checker capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "type-definition-consistency-checker-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_e9qkPrv0oxwaJFM5IRMYH0SAdmGX3uUy7kc4Yxip/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 Type Definition Consistency Checker in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Type Definition Consistency Checker owners hand off.

This MCP is built for engineers working in full-stack environments where data structures must match across different languages.

  • 01

    Frontend Engineers

    They use it to ensure TypeScript interfaces match the backend API expectations.

  • 02

    Backend Engineers

    They use it to verify that Pydantic models stay aligned with the frontend's Zod schemas.

  • 03

    Full-stack Developers

    They use it to prevent runtime errors caused by structural mismatches in their data models.

FAQ

Questions Type Definition Consistency Checker owners ask.

  • 01

    What kind of schemas does this MCP support?

    It is designed to work with TypeScript interfaces, Zod schemas, and Pydantic models.

  • 02

    How does it find errors in my code?

    It uses AST-based parsing to analyze the actual structure of your type definitions rather than just performing a text search.

  • 03

    Can I use this with Claude or Cursor?

    Yes, you can use this MCP with any MCP-compatible client including Claude, Cursor, and Windsurf.

  • 04

    What does it mean to detect structural drift?

    It means the capability finds instances where your frontend and backend data structures no longer match, such as missing fields or different data types.

  • 05

    Does this MCP host my code?

    No, Vinkius hosts the MCP itself. Your code remains in your environment, and the MCP capabilities interact with it through your AI client.

  • 06

    What types of definitions can I check?

    The capability supports typescript_interface, zod_schema, and pydantic_model formats.

  • 07

    How does the capability detect errors?

    It uses deterministic AST parsing to extract field names, types, and optionality markers, then performs set comparison across your provided definitions.

  • 08

    Can I use this for a single Pull Request review?

    Yes, you can use the compare_definitions capability to perform a targeted comparison between a base definition and a target definition.

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