Type Definition Consistency CheckerをAIに接続

最速日

567ms

最遅日

782ms

14日間の傾向

改善傾向-5%

Type Definition Consistency Checker Connector

準備完了です。MCPクライアントを選択し、セットアップ手順に従ってください。

コネクタリンクhttps://edge.vinkius.com/vk_preview_e9qkPrv0oxwaJFM5IRMYH0SAdmGX3uUy7kc4Yxip/mcpコピー

Claude Desktop

以下の手順で数秒で接続できます。

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.

設定 · claude_desktop_config.jsonコピー

{
  "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

各クライアントの手順ガイドはこちらです。 接続方法

Claude向けのガイド付きセットアップ？ Type Definition Consistency CheckerをClaudeや他のAIに設定する

このConnectorが対応するすべてのAIクライアントを見る ↑

• 01

  フルスタックエンジニア

  フロントエンドのTypeScriptとバックエンドのPython/Pydantic間の型の一貫性を維持したい開発者。

• 02

  QAエンジニア

  スキーマ定義の整合性を自動化されたプロセスで検証したいテスト担当者。

• 03

  システムアーキテクト

  アプリケーション全体のデータ構造のドリフトを防ぎ、設計の正確性を保ちたい設計者。

• 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.

• 

  Zod Schema Error Flattener AIコネクタ

  Transforms complex, deeply nested ZodError objects into flat, field-centric error dictionaries for UI consumpt

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• 

  Exact Type Inference Validator AIコネクタ

  Analyze TypeScript source code to detect implicit 'any', type assertions, and unannotated declarations.

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• 

  JSON Schema Validator and Flattener AIコネクタ

  Strictly validate JSON against schemas and flatten nested structures using dot notation.

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• 

  JSON Schema Function Call Validator AIコネクタ

  Validates raw LLM text outputs against JSON Schemas to detect missing parameters, type mismismatches, and hall

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