Shadcn-native Design CI for Tailwind apps with registry export and MCP UI tools.
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io.github.sarveshsea/memoire is an MCP server that shadcn-native Design CI for Tailwind apps with registry export and MCP UI tools. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 87/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"memoire": {
"args": [
"mcp",
"start",
"--no-figma"
],
"command": "memi"
}
}
}Are you the author?
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Shadcn-native Design CI for Tailwind apps with registry export and MCP UI tools.
This server supports HTTP transport. Be the first to test it - help the community know if it works.
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No known CVEs.
Checked shadcn against OSV.dev.
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The design layer for agentic AI.
Give your coding agent an interface brief before it edits. Memi maps the UI already in your repository, surfaces file-anchored accessibility and design-system risks, and gives you a deterministic check to rerun before merge. Start with the CLI, then add the same gate to every pull request.
Memi Studio is available today; Memi Canvas is currently in development. No account, API key, Figma file, global install, or daemon is required for the first audit.
Start with your next interface · Get Memi Studio · Read the research
Run one non-destructive audit in any frontend repository. It needs no account, API key, Figma file, global install, or daemon.
npx -y @memi-design/cli@latest diagnose . --json --no-write --fail-on none
The result carries normalized finding IDs, confidence, provenance, and file:line evidence so an agent can act on a specific finding instead of guessing.
Give the same context to your coding agent:
npx skills add memi-design/memi --skill audit-frontend-design
Then ask:
Audit this frontend before editing it. Prioritize the five changes that will matter most to users, reuse the existing system, and verify the result after the patch.
If Memi catches a real interface issue in your project, share the finding. Real reports are the most useful signal for what to improve next.
Local source diagnosis uses deterministic rules: no model call, API key, or model fee. It checks the repository you provide and returns findings your agent can verify. Installation, CPU time, CI runners, and any agent you choose still have costs. The published research has not established an end-to-end dollar or token savings advantage.
Start with one diagnosis, address the highest-confidence finding, and rerun the same check. Use --agent-context for a bounded file index instead of sending a whole repository to a model. Its routing is heuristic; a smaller context is not proof of a cheaper successful task. --files scopes reported findings without launching Git; it still scans the tree for aggregate statistics.
Published beta: Install the exact 2.8.0-beta.2 package for the 2.8 frontend workflow. Stable remains 2.7.9; the beta is not a stable release. See current release state and known limitations.
The beta2 npm release record identifies its published source and immutable artifact evidence. The [beta1 npm release r