Dify
This Dify MCP server, developed by an unnamed creator, integrates with the Dify API to enable AI-driven workflow execution through the Model Context Protocol. Built with Python and leveraging libraries like httpx and mcp, it provides tools for interacting with Dify workflows and applications. The server implements environment-based configuration for flexible API key management. By abstracting Dify API interactions into a standardized MCP interface, it enables AI systems to easily trigger and manage Dify workflows and applications. This implementation is valuable for applications requiring programmatic access to Dify capabilities, facilitating use cases such as automated task execution, multi-step data processing, and AI-driven decision making across various domains.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-01.
Scan details: Circle-IR · 2026-09-01 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- productivity
- Source
- PulseMCP
- Repository
- github.com/yanxingliu/dify-mcp-server
- Author type
- human
- Last scanned
- 2026-09-01
- Updated
- 2026-09-01
Use via MCP
Resolve Dify from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.