mcp-server-dify

Name: mcp-server-dify
Author: yuru-sha

@yuru-sha

Repository

About mcp-server-dify

Sample MCP Server for Dify AI

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

FAQ from mcp-server-dify

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.

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>.

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.

Does mcp-server-dify support streaming?

Yes, streaming response support is listed as a feature.

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.

Comments

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