mcp-server-dify

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.