Streamline tasks with Dify Workflow—powerful workflow automation software for automated approval and advanced workflow a
Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
Obsidian
Connect Obsidian vaults for natural language queries and secure note updates with seamless Obsidian integration.
Amicus MCP Server
Amicus MCP Server: state persistence for AI coding assistants—preserves shared context, summaries, next steps and active
Asana
MCP server for Asana — enables Claude to interact with Asana data and workflows.
Repomix
Optimize your codebase for AI with Repomix—transform, compress, and secure repos for easier analysis with modern AI tool
Confluence
Seamlessly enhance your workflow by integrating Confluence with Jira for direct documentation access and powerful conten
Dify Workflow has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Useful MCP listing: Dify Workflow is the kind of server we cite when onboarding engineers to host + tool permissions.
We evaluated Dify Workflow against two servers with overlapping tools; this profile had the clearer scope statement.
Dify Workflow reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We wired Dify Workflow into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Dify Workflow is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, Dify Workflow benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Dify Workflow is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated Dify Workflow against two servers with overlapping tools; this profile had the clearer scope statement.
Useful MCP listing: Dify Workflow is the kind of server we cite when onboarding engineers to host + tool permissions.
showing 1-10 of 39
Share your MCP server with the developer community
Select a client to integrate this server.
Claude Desktop configuration
{
"mcpServers": {
"dify": {
"command": "npx",
"args": [
"@tonlab/dify-mcp-server"
],
"env": {
"DIFY_BASE_URL": "https://api.dify.ai/v1",
"DIFY_API_KEYS": "app-FirstAPIKeyHere,app-SecondAPIKeyHere,app-ThirdAPIKeyHere"
}
}
}
}Connects Claude to Dify Workflow APIs, allowing you to execute Dify workflows directly from Claude conversations. Supports multiple API keys for accessing different workflow collections.
Dify Workflow is a community-built MCP server published by tomokiishimine that provides AI assistants with tools and capabilities via the Model Context Protocol. Streamline tasks with Dify Workflow—powerful workflow automation software for automated approval and advanced workflow a It is categorized under productivity, developer tools.
You can install Dify Workflow in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
A tool server for easy integration with Dify Workflow using the Model Context Protocol (MCP).
To use with Claude Desktop App, add the following settings to Claude's configuration file:
Add to %AppData%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"dify-workflow": {
"command": "npx",
"args": ["@tonlab/dify-mcp-server"],
"env": {
"DIFY_BASE_URL": "https://your-dify-endpoint",
"DIFY_API_KEY": "your-api-key-here"
}
}
}
}
You can now configure multiple Dify API keys, which will create multiple tools (one per API key):
{
"mcpServers": {
"dify": {
"command": "npx",
"args": ["@tonlab/dify-mcp-server"],
"env": {
"DIFY_BASE_URL": "https://api.dify.ai/v1",
"DIFY_API_KEYS": "app-FirstAPIKeyHere,app-SecondAPIKeyHere,app-ThirdAPIKeyHere"
}
}
}
}
Each API key will be exposed as a separate tool in Claude, with a distinct number appended to the tool name.
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"dify-workflow": {
"command": "npx",
"args": ["@tonlab/dify-mcp-server"],
"env": {
"DIFY_BASE_URL": "https://your-dify-endpoint",
"DIFY_API_KEY": "your-api-key-here"
}
}
}
}
Same multiple API key configuration as described above works on macOS/Linux as well.
MIT
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Chrome DevTools MCP
AI-driven control of live Chrome via Chrome DevTools: browser automation, debugging, performance analysis and network mo