Dify Workflow▌
by tomokiishimine
Streamline tasks with Dify Workflow—powerful workflow automation software for automated approval and advanced workflow a
Connects Claude with Dify Workflow to expose workflow capabilities as tools, enabling structured automation through dynamic parameter retrieval and multi-workflow support.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Automating business processes through Claude
- / Integrating existing Dify workflows into AI conversations
- / Running multi-step workflows without leaving Claude
- / Teams using Dify for workflow automation
capabilities
- / Execute Dify workflows from Claude
- / Retrieve workflow parameters dynamically
- / Configure multiple Dify API keys
- / Access different Dify endpoints
- / Run structured automation workflows
- / Pass parameters to workflow executions
what it does
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.
about
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.
how to install
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.
license
MIT
Dify Workflow is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Dify Workflow MCP Tool Server
A tool server for easy integration with Dify Workflow using the Model Context Protocol (MCP).
Features
- MCP protocol implementation enabling bidirectional communication with Claude
- Utilizes Dify Workflow as a tool
- Dynamically retrieves and displays Dify Workflow parameters
- Simple configuration using environment variables
- NEW: Support for multiple Dify API keys
Prerequisites
- Node.js 16 or higher
- npm 7 or higher
- Access rights to Dify Workflow (API Key)
Integration with Claude Desktop App
To use with Claude Desktop App, add the following settings to Claude's configuration file:
Windows
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"
}
}
}
}
Using Multiple API Keys (NEW)
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.
macOS/Linux
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.
License
MIT
FAQ
- What is the Dify Workflow MCP server?
- Dify Workflow is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Dify Workflow?
- This profile displays 39 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
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
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ 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.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.6★★★★★39 reviews- ★★★★★Chaitanya Patil· Dec 4, 2024
Dify Workflow has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Yuki Khanna· Dec 4, 2024
Useful MCP listing: Dify Workflow is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Piyush G· Nov 23, 2024
We evaluated Dify Workflow against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Yuki Desai· Nov 23, 2024
Dify Workflow reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Shikha Mishra· Oct 14, 2024
We wired Dify Workflow into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Amina Gill· Oct 14, 2024
Dify Workflow is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Kofi Gupta· Oct 14, 2024
According to our notes, Dify Workflow benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Isabella Chawla· Sep 25, 2024
Dify Workflow is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Yusuf Rao· Sep 21, 2024
We evaluated Dify Workflow against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Tariq Thomas· Sep 9, 2024
Useful MCP listing: Dify Workflow is the kind of server we cite when onboarding engineers to host + tool permissions.
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