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  3. AINDF
A
Health: ActiveRecent health check succeeded.Last checked 10/14/2026, 2:00:55 PM

AINDF

InstallableWe know how to install it, but have not yet seen it complete a handshake. User RatingsBe the first to rate and review this MCP server!
View Repository26 GitHub StarsTotal stargazers on GitHub for the source repository (26 stars).
design-systemui-validationdeveloper-toolsstdio

Read-only MCP server for querying one AINDF design-system bundle and validating screen configurations.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "aindf": {
      "command": "npx",
      "args": [
        "-y",
        "@ai-native-design-framework/kit"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Overview

The AINDF MCP server connects an AI agent to a bundled design system and exposes its defined components, slots, modifiers, and presets. Agents can use these lookups to author screen configurations pinned to a specific design-system version, then call screen validation to reject unsupported properties or values. Build the bundle from seven design-system sources, configure the server as a stdio MCP process, and reach for it when generated screens must stay within an existing design system.

Use cases

β€’Query a design system before generating screen configurations
β€’Validate screens against bundled components and properties
β€’Keep generated UI pinned to a design-system version
β€’Detect unsupported values before building a screen

Key features

β€’Read-only access to one design-system bundle
β€’Component, slot, modifier, and preset lookups
β€’Screen validation with validate-screen
β€’Version-pinned screen configurations
β€’stdio MCP deployment through the AINDF kit

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by AINDF.

Extracted Tool Capabilities
Read-only access to one design-system bundle
Component, slot, modifier, and preset lookups
Screen validation with validate-screen
Version-pinned screen configurations
stdio MCP deployment through the AINDF kit

How AINDF works

What the AINDF MCP server does

The AINDF MCP server gives an AI agent a read-only view of one bundled design system. Instead of allowing the agent to invent HTML, CSS, or unsupported component values, it provides the information needed to construct screen configurations from the bundle. The configuration is tied to one version of the design system.

The bundle describes seven source areas: tokens, taxonomy, slots, applicability, presets, components, and bindings. Agents can query the available components, slots, modifiers, and presets, then use validate-screen to check whether a proposed screen follows the bundle. Invalid configurations are rejected with errors such as a component property that the design system does not define. The server does not update the design system; missing capabilities must be added to the design system separately and with approval.

How it works

First, the design-system sources are listed in aindf.config.json. The AINDF kit checks that configuration and bundles the sources into one aindf.bundle.json file. The MCP process receives the bundle path and serves it to the connected agent over stdio.

A typical workflow is:

  • The agent asks what components, slots, modifiers, and presets are available.
  • The agent creates a screen configuration pinned to the bundle version.
  • The agent calls validate-screen.
  • If validation fails, the agent reports the missing or unsupported definition instead of adding an ad hoc value.
  • Once validation passes, a builder can create the screen from the approved configuration.

Updating the design system requires producing a new bundle version. Existing screens can then be moved to that version with the repository's repin workflow.

Setup and configuration

The AINDF MCP server requires Node.js 20.10 or newer. The kit can be run from a repository clone or through npm. From the design-system directory, check the source configuration and create a bundle:

Terminal
npx -y @ai-native-design-framework/kit check aindf.config.json
npx -y @ai-native-design-framework/kit bundle aindf.config.json --out aindf.bundle.json

Register the resulting file with Claude Code using:

Terminal
claude mcp add aindf -- npx -y @ai-native-design-framework/kit mcp /absolute/path/to/aindf.bundle.json

Other agents can run the same node or npx MCP command as a stdio server in their MCP settings. The repository also provides a Claude Code plugin, and the aindf-screen-author skill can be installed with the skills CLI for agents that do not use that plugin.

Tools and capabilities

The AINDF MCP server supports read-only discovery of the bundle's design-system definitions. Its documented agent-facing operations include lookups for:

  • Components
  • Slots
  • Modifiers
  • Presets
  • Screen validation through validate-screen

These capabilities are intended for screen configuration authoring. They do not imply that the server can edit source files, change the design system, or accept arbitrary CSS values.

Limitations and notes

The server is designed around one AINDF bundle at a time, so the screen configuration must remain pinned to that bundle's version. A configuration can only use what the bundle exposes. If a required component, property, token, or other definition is absent, validation will not make it available; the design system must be updated and rebuilt instead.

The MCP command is a stdio server command, and the bundle path must be absolute in the documented setup. The repository describes the server as read-only. Screen building is a separate step from querying and validation, while the optional plugin supplies authoring instructions rather than changing the server's underlying bundle.

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
26
Stargazers on the source repository.
Last commit
3d ago
Most recent push to the default branch.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about AINDF

AINDF is an MCP server that connects an AI agent to one bundled design system and exposes lookups for components, slots, modifiers, and presets plus screen validation. It helps agents author screen configurations pinned to that bundle, refusing configurations that use values or properties the design system does not define.

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
LicenseMIT
ClientsClaude Desktop, Cursor, Cline / VS Code, Windsurf, Claude Code, VS Code (GitHub Copilot), Zed, OpenAI Codex CLI, Gemini CLI, JetBrains AI Assistant, Roo Code, Continue, LM Studio
Last updatedOct 14, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars26
GitHub Star CountTotal stargazers on GitHub representing community popularity (26 stars).
Last commit3d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Oct 11, 2026
44Quality signal: Fair Β· 44/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity7/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned just now via OSV.dev Β· @ai-native-design-framework/kit (npm)

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