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MCP Server Dify

@yuru-sha

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

yuru-sha

MCP Server Dify について

Sample MCP Server for Dify AI

MCP Server Dify の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-server-dify": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "mcp/dify",
        "https://your-dify-api-endpoint",
        "your-dify-api-key"
      ]
    }
  }
}

MCP Server Dify のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is mcp-server-dify?

mcp-server-dify is a Model Context Protocol server that enables LLMs to interact with Dify AI’s chat completion API. Written in TypeScript, it provides a standardized interface for chat, streaming responses, and conversation context.

How to use mcp-server-dify?

Install via Docker (make docker then docker run -i --rm mcp/dify <endpoint> <key>) or run directly with npx. Configure it in Claude Desktop by adding the endpoint and API key to your claude_desktop_config.json. Invoke its tools, such as the meshi-doko tool for restaurant recommendations, by supplying the required parameters (LOCATION, BUDGET, query, optional conversation_id).

Key features of mcp-server-dify

  • Integration with Dify AI chat completion API
  • Restaurant recommendation tool (meshi-doko)
  • Support for maintaining conversation context
  • Streaming response support
  • TypeScript implementation with CI, linting, and formatting
  • Docker and npx deployment options

Use cases of mcp-server-dify

  • Querying Dify AI for restaurant recommendations based on location and budget
  • Building conversational agents that maintain multi-turn context
  • Enabling LLMs to access Dify AI’s specialized chat capabilities through a standardized protocol
  • Rapid prototyping with Docker or direct CLI invocation

よくある質問

1

What are the prerequisites for using mcp-server-dify?

You need a Dify AI API endpoint URL and an API key. Either Docker (to run the container) or Node.js (to use npx) is required.

2

How do I install and run mcp-server-dify with Docker?

Build the image with `make docker`, then run: `docker run -i --rm mcp/dify <your-dify-api-endpoint> <your-dify-api-key>`.

3

What does the meshi-doko tool do?

It is a restaurant recommendation tool that interfaces with Dify AI. It accepts a location, budget, query, and optional conversation ID to maintain context across calls.

4

Does mcp-server-dify support streaming?

Yes, streaming response support is listed as a feature.

5

How should I secure my API credentials?

Keep your API key private, use HTTPS for the endpoint, and never commit the key to version control.

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