D

Dify

This project provides a devcontainer configuration, supporting the rapid setup of a unified development environment in GitHub Codespaces and VS Code, including frontend and backend initialization configurations, to solve the problem of environment differences.
2 points
13

What is Dify Devcontainer?

Dify Devcontainer provides a ready - to - use development environment inside a Docker container, with all necessary tools and configurations pre - installed for both frontend and backend development.

How to use Dify Devcontainer?

You can start developing immediately by opening the project in GitHub Codespaces or VS Code Dev Containers. The environment automatically initializes both frontend and backend setups when the container starts.

When to use

Ideal for developers who want to quickly start contributing to Dify without spending time on environment setup, or teams who need consistent development environments across all members.

Key Features

Unified EnvironmentPre - configured development environment ensures consistency across all team members
Quick SetupGet started with development in minutes without manual configuration
Isolated WorkspaceDevelopment environment runs in a container separate from your host system

Pros and Cons

Advantages
Consistent environment for all developers
Quick onboarding for new team members
Isolation from host system prevents conflicts
Limitations
Requires basic knowledge of Docker and VS Code
May have slightly slower performance than native environment
Limited by container resource allocations

Getting Started

Open in Codespaces
Click the 'Open in GitHub Codespaces' button to launch the environment in your browser
Open in VS Code
If using VS Code, click the 'Open in Dev Containers' button to launch locally
Wait for initialization
The container will automatically set up both frontend and backend environments

Usage Scenarios

New Developer OnboardingA new team member can start contributing immediately without spending days setting up their environment
Environment TroubleshootingWhen encountering environment - specific bugs, the team can verify if they reproduce in the standard container

Frequently Asked Questions

Why do I see an error about '/signin' endpoint?
How is this different from local development?
Can I customize the devcontainer?

Additional Resources

GitHub Codespaces Documentation
Official documentation for GitHub Codespaces
VS Code Dev Containers
Guide to using Dev Containers in VS Code
Dify GitHub Repository
Main project repository
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
S
Search1api
The Search1API MCP Server is a server based on the Model Context Protocol (MCP), providing search and crawling functions, and supporting multiple search services and tools.
TypeScript
343
4 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
830
4.3 points
M
MCP Alchemy
Certified
MCP Alchemy is a tool that connects Claude Desktop to multiple databases, supporting SQL queries, database structure analysis, and data report generation.
Python
325
4.2 points
P
Postgresql MCP
A PostgreSQL database MCP service based on the FastMCP library, providing CRUD operations, schema inspection, and custom SQL query functions for specified tables.
Python
112
4 points
M
MCP Scan
MCP-Scan is a security scanning tool for MCP servers, used to detect common security vulnerabilities such as prompt injection, tool poisoning, and cross-domain escalation.
Python
616
5 points
A
Agentic Radar
Agentic Radar is a security scanning tool for analyzing and assessing agentic systems, helping developers, researchers, and security experts understand the workflows of agentic systems and identify potential vulnerabilities.
Python
557
5 points
C
Cloudflare
Changesets is a build tool for managing versions and releases in multi - package or single - package repositories.
TypeScript
1.5K
5 points
E
Edgeone Pages MCP Server
EdgeOne Pages MCP is a service that quickly deploys HTML content to EdgeOne Pages via the MCP protocol and obtains a public URL
TypeScript
254
4.8 points
Featured MCP Services
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
141
4.5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
830
4.3 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
1.7K
5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
87
4.3 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
6.7K
4.5 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
567
5 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
754
4.8 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
5.2K
4.7 points
AIbase
Zhiqi Future, Your AI Solution Think Tank
© 2025AIbase