OpenAPI Context Window PackerをAIに接続

最速日

583ms

最遅日

866ms

14日間の傾向

改善傾向-5%

OpenAPI Context Window Packer 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_XMZvUjc3wLVnJZVkg6dLaL15NgLbiiNTRgEG82fO/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 — OpenAPI Context Window Packer capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "openapi-context-window-packer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_XMZvUjc3wLVnJZVkg6dLaL15NgLbiiNTRgEG82fO/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？ OpenAPI Context Window Packer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

  AI Engineer

  They hand off massive API documentation to the MCP to create lean context for their agents.

• 02

  Backend Developer

  They use it to test if their API specs are being correctly interpreted by AI clients.

• 03

  DevOps Engineer

  They use it to manage the token costs and performance of LLM-based automation capabilities.

• 01

  How does this MCP reduce token counts?

  It uses the compress_openapi_spec capability to remove paths you don't need and strips out any components that aren't actually used by your target endpoints.

• 02

  Will the compressed spec still be valid?

  Yes, the MCP uses dependency tracing to ensure that all required schemas and components remain in the file so the API remains functional.

• 03

  Which AI clients can use this MCP?

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

• 04

  Can I check if an endpoint exists before compressing?

  Yes, you can use the analyze_endpoint_coverage capability to verify that your target endpoints are present in the specification.

• 05

  Does this work with Swagger files?

  Yes, it is designed to handle both OpenAPI and Swagger specifications.

• 06

  How does the compression work?

  The engine uses deterministic pruning. It removes all paths not in your targetEndpoints and then traces $ref pointers to remove any schemas that are no longer reachable, ensuring the resulting spec is structurally valid.

• 07

  Will my API specification break after compression?

  No. The capability ensures schema integrity by performing a graph traversal. Any component or schema required by your target endpoints is strictly preserved.

• 08

  Can I control the size of the output?

  Yes. Using compress_openapi_spec, you can set a maxTokenBudget. The engine will iteratively truncate description fields until the specification fits within your specified budget.

• 

  Dynamic Context Window Packer AIコネクタ

  Optimally packs retrieved documents into LLM context windows using a greedy knapsack algorithm.

  表示
• 

  Context Window Eviction Planner AIコネクタ

  A deterministic engine to manage LLM context windows by calculating optimal message eviction.

  表示
• 

  LLM Context Window Budgeter AIコネクタ

  Monitor and predict LLM context window exhaustion with precision token forecasting.

  表示
• 

  Claude Context Window Budget Tracker AIコネクタ

  Monitors and enforces token consumption budgets to prevent context window saturation.

  表示

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  Context Window Optimizer AIコネクタ

  Optimizes LLM context windows by selecting the most relevant and recent information within token limits.

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• 

  Context Window Compression Calculator AIコネクタ

  Mathematically model token reduction strategies and quality trade-offs.

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• 

  Context Window Economics Optimizer AIコネクタ

  Calculate the financial and performance impact of LLM context management strategies.

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• 

  Context Window Token Estimator AIコネクタ

  Calculate exact token counts and payload distribution for AI agent context windows.

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