daisyui-mcp
Provides a local MCP (Model Context Protocol) server that exposes DaisyUI component documentation as MCP tools. It can fetch DaisyUI’s public `llms.txt` and store component docs as local Markdown, then serve two tools: list components and get component documentation.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Intended for local use; no auth is documented. If run in Docker or bound to a network port, you should restrict access. It fetches DaisyUI `llms.txt` and writes local files—ensure supply-chain and integrity considerations are handled (pinning, checksums, trust of upstream). No information is provided about dependency vulnerabilities, TLS, or secret handling practices.
⚡ Reliability
Best When
You run a local agent that needs fast, tool-based access to DaisyUI component descriptions and examples, and you can periodically update the local docs.
Avoid When
You need strict security controls (authZ, secrets management, tenant isolation) or you plan to expose the MCP server to untrusted networks/users without compensating controls.
Use Cases
- • LLM/agent-assisted UI generation using DaisyUI component docs
- • Retrieval of component class syntax and examples for specific DaisyUI components
- • Offline/local agent workflows that avoid sending full documentation to the model
- • Customization of component docs by editing local Markdown
Not For
- • Production hosted, internet-facing use without additional hardening
- • Scenarios requiring authenticated/role-based access control for documentation tools
- • Use as a general DaisyUI component renderer or CSS/JS execution environment
- • Teams needing audited/legal-approved documentation ingestion pipelines
Interface
Authentication
No authentication mechanism is described; intended use appears to be local execution (Python script or Docker). If exposed remotely, you must add network/firewall protections or run behind an authenticated gateway.
Pricing
No hosted service pricing described; this is a local MCP server.
Agent Metadata
Known Gotchas
- ⚠ Tool set appears limited to `list_components` and `get_component`; agents may need to handle missing components or outdated local docs
- ⚠ If docs are not yet fetched (first run), `get_component` may fail until `update_components.py` has been run
- ⚠ No documented rate-limit or server-side throttling behavior; agents should avoid aggressive polling if the server is resource-constrained
Alternatives
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Scores are editorial opinions as of 2026-03-30.