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Aceternity MCP

Model Context Protocol server for Aceternity UI components

Discover, search, and install 106 Aceternity UI components from your AI assistant. Generate full page layouts, get context-aware recommendations, and install everything with a single command.

PyPI npm Python MCP License Tests


Install

pipx install aceternity-mcp
aceternity-mcp install

Restart your AI tool. Done.

Related MCP server: aceternityui-mcp

What It Does

Your AI assistant gets 11 tools for working with Aceternity UI:

Tool

What it does

generate_page_layout

Generate a full page layout with sections, components, and install commands

search_components

Full-text search across names, descriptions, tags, categories

recommend_components

Get recommendations for a use case or design goal

recommend_combination

Get component suggestions for each page section

match_components_to_project

Match components to a whole project description

list_components

List all 106 components with optional filters

list_categories

Show all 17 categories with component counts

get_component

Get full metadata for a single component

get_category

Get all components in a category

install_component

Get install command, dependencies, and setup steps

filter_by_scores

Filter by visual intensity, animation, performance, etc.

Page Layout Generator

The standout feature. Ask your AI to generate a complete page layout and it returns:

  • Ordered sections with recommended components for each role

  • Design tone detection (dark, premium, modern, minimal, etc.)

  • Section-specific scoring using 17 role profiles

  • De-duplicated components across sections

  • Implementation notes for every section

  • Batch install command for all components at once

  • Performance estimate and dependency summary

7 page types: landing, saas, dashboard, portfolio, ecommerce, blog, documentation

Example prompts:

"Generate a page layout for a dark premium AI SaaS landing page"
"Build me a fintech dashboard layout with analytics"
"Create a portfolio page with 3D effects and scroll animations"
"Design an e-commerce store layout for a clothing brand"

Scoring signals per component:

Signal

Description

Section-role category match

17 role profiles with preferred categories

Section-role tag match

Role-specific tag boosting

Section score weights

Tuned dimension weights per role

Archetype context

Page-level scoring (SaaS, dashboard, portfolio, etc.)

Text relevance

User description keyword matching

Design tone coherence

Boosts components matching detected tones

Dependency reuse

Bonus for shared npm dependencies

Example Prompts

"Show me subtle dark background effects with low performance impact"
"Recommend a navbar + hero + CTA combination for a SaaS landing page"
"Find highly customizable card components for testimonials"
"Give me low-motion components suitable for a dashboard"
"Install Spotlight and show me what dependencies are needed"
"What components work well for dark mode dashboards?"
"Search for animated text effects"
"Filter components with visual intensity above 7 and low performance impact"

Supported AI Tools

Tool

Auto-configured

Claude Desktop

Yes

Claude Code CLI

Yes

Cursor

Yes

Cline (VS Code)

Yes

Windsurf

Yes

OpenCode

Yes

Run aceternity-mcp install and all detected tools are configured automatically.

Manual Configuration

All tools use the same server command:

{
  "mcpServers": {
    "aceternity-ui": {
      "command": "aceternity-mcp-server",
      "args": []
    }
  }
}

Tool

Config file

Cursor

~/.cursor/mcp.json

Claude Code

~/.claude/mcp.json

Cline

VS Code extension settings

Windsurf

~/.codeium/windsurf/mcp_config.json (uses mcp_servers / aceternity_ui)

OpenCode

~/.opencode/mcp.json

CLI Commands

Command

Description

aceternity-mcp install

Interactive setup wizard

aceternity-mcp status

Show installation health

aceternity-mcp update

Check for and install updates

aceternity-mcp repair

Fix registry, configs, or permissions

aceternity-mcp diagnose

Output JSON diagnostics

aceternity-mcp uninstall

Remove from all AI tools

aceternity-mcp --version

Show version

# Repair only the registry
aceternity-mcp repair --registry

# Repair only client configs
aceternity-mcp repair --configs

# Non-interactive update
aceternity-mcp update -y

Alternative Install Methods

Docker

docker pull ghcr.io/devinoldenburg/aceternity-mcp
docker run -i ghcr.io/devinoldenburg/aceternity-mcp

npm (wrapper)

npx aceternity-mcp-server

Requires the Python package installed separately (pipx install aceternity-mcp).

pip

pip install aceternity-mcp

From source

git clone https://github.com/devinoldenburg/aceternity-mcp.git
cd aceternity-mcp
pipx install .

Component Registry

106 components across 17 categories:

Category

Count

Examples

Backgrounds

18

Aurora, Beams, Grid, Spotlight, Vortex

Cards

15

3D Card, Card Hover, Expandable Card

Text Effects

13

Typewriter, Text Generate, Gradient Text

Scroll Effects

11

Parallax, Scroll Reveal, Tracing Beam

Visualization

9

Globe, World Map, SVG Mask

Hero Sections

8

Hero Parallax, Spotlight, Lamp Effect

Navigation

7

Floating Dock, Navbar Menu

Layout

81

Bento Grid, Container Scroll, Timeline

Forms

6

Input, Placeholders, Multi-Step

3D Effects

5

3D Card, 3D Pin, Globe

Each component includes: detailed description, purpose, behavior, visual characteristics, design tone, difficulty level, dependencies, install command, compatibility flags, and 7 scoring dimensions.

Scoring Dimensions

Every component is rated 1-10 on:

Dimension

What it measures

Visual Intensity

How visually dominant (1 = subtle, 10 = dramatic)

Animation Intensity

Amount of motion (1 = static, 10 = heavy animation)

Layout Importance

Structural criticality (1 = decorative, 10 = essential)

Customization Ease

Flexibility (1 = rigid, 10 = very configurable)

Landing Page Fit

Suitability for landing pages

Dashboard Fit

Suitability for dashboards

Performance Impact

Runtime cost (1 = lightweight, 10 = heavy)

Development

git clone https://github.com/devinoldenburg/aceternity-mcp.git
cd aceternity-mcp
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

# Lint + type check
ruff check src/ tests/
mypy src/aceternity_mcp/ tests/

# Validate registry
python scripts/validate_registry.py

Quality

  • 172 tests, 9 archetypes, 17 section role profiles, 7 page templates

  • ruff lint + format, mypy strict, bandit security scan

  • CI: quality gates on every push, auto-publish on release

Security

  • Metadata only: No Aceternity source code, documentation, or images in this repository

  • No secrets: No API keys or credentials

  • Isolated: pipx provides sandboxed virtual environments

  • Install commands: Point to Aceternity's official @aceternity shadcn registry

Troubleshooting

Command not found -- Run pipx ensurepath and restart your terminal.

Registry not found -- Run aceternity-mcp repair or pipx reinstall aceternity-mcp.

MCP server not connecting -- Run aceternity-mcp diagnose and check the output. Repair configs with aceternity-mcp repair --configs.

Update issues -- Run pipx upgrade aceternity-mcp or pipx reinstall aceternity-mcp.

License

MIT -- see LICENSE.

Available Tools

12 tools
filter_by_scoresA

Filter components by numeric scoring thresholds (1-10 scale).

All parameters are optional. Only components passing every specified threshold are returned.

Scoring dimensions:

  • visualIntensity: How visually dominant (1=subtle, 10=dramatic)

  • animationIntensity: How much animation/motion (1=static, 10=heavy)

  • layoutImportance: How critical to page structure (1=decorative, 10=essential)

  • customizationEase: How easy to customise (1=rigid, 10=very flexible)

  • landingPageFit: Suitability for landing pages (1=poor, 10=perfect)

  • dashboardFit: Suitability for dashboards (1=poor, 10=perfect)

  • performanceImpact: Runtime cost (1=lightweight, 10=heavy)

Args: min_visual_intensity: Minimum visual intensity (1-10) max_visual_intensity: Maximum visual intensity (1-10) min_animation_intensity: Minimum animation intensity (1-10) max_animation_intensity: Maximum animation intensity (1-10) min_landing_page_fit: Minimum landing page fit (1-10) min_dashboard_fit: Minimum dashboard fit (1-10) max_performance_impact: Maximum performance impact (1-10) min_customization_ease: Minimum customization ease (1-10) include_pro: Include pro components (default True)

Inputs: min_visual_intensity, max_visual_intensity, min_animation_intensity, max_animation_intensity, +5 more. Returns: result

generate_page_layoutA

Generate a complete page layout with component recommendations.

Analyses the description to detect the page type, selects the best template, and fills each section with recommended components. Returns an ordered layout with install commands and dependency summary.

Supported page types (auto-detected if not specified):

  • landing: Conversion-focused landing page

  • saas: SaaS product marketing page

  • dashboard: Data-rich admin dashboard

  • portfolio: Creative portfolio or showcase

  • ecommerce: E-commerce product store

  • blog: Blog or content publication

  • documentation: Documentation or knowledge base

Example descriptions:

  • "premium AI SaaS product page with dark theme"

  • "fintech dashboard with analytics and charts"

  • "designer portfolio with 3D effects"

  • "online clothing store with product grid"

  • "developer blog with code examples"

Args: page_description: Free-text description of the page to build page_type: Explicit page type (auto-detected if omitted) include_pro: Include pro components (default True) components_per_section: Components per section (default 2, max 10)

Inputs: page_description (required), page_type, include_pro, components_per_section. Returns: result

get_cache_statsA

Get search cache statistics for monitoring and debugging.

Returns cache performance metrics including:

  • size: Current number of cached entries

  • max_size: Maximum cache capacity

  • hits: Number of cache hits

  • misses: Number of cache misses

  • evictions: Number of evicted entries

  • hit_rate_percent: Cache hit rate as percentage

Use this to monitor cache effectiveness and tune cache parameters.

Inputs: no named parameters. Returns: result

get_categoryA

Get all components in a specific category.

Returns the category info and full summaries of every component that belongs to it.

Args: slug: Category slug (e.g. "hero-sections", "backgrounds", "cards")

Inputs: slug (required). Returns: result

get_componentA

Get the full detailed entry for a single component.

Returns ALL metadata including the 60+ word detailed description, purpose, behavior, visual characteristics, dependencies, install commands, props, compatibility, and scoring.

Args: slug: Component slug (e.g. "spotlight", "bento-grid", "hero-parallax")

Inputs: slug (required). Returns: result

install_componentA

Get full installation instructions for a component.

Returns the install command, dependencies, registry URL, documentation link, and step-by-step setup instructions.

Args: slug: Component slug (e.g. "spotlight", "sidebar", "bento-grid")

Inputs: slug (required). Returns: result

list_categoriesA

List all component categories with descriptions and component counts.

Inputs: no named parameters. Returns: result

list_componentsA

List all available Aceternity UI components.

Optionally filter by category slug. Returns a compact summary for each component (slug, name, category, tags, summary).

Args: category: Optional category slug (e.g. "hero-sections") include_pro: Include pro-only components (default: True)

Inputs: category, include_pro. Returns: result

match_components_to_projectA

Match components to a whole project description.

Similar to recommend_components but biased toward layout-critical components and returns more results for full project planning.

Args: project_description: Project description (e.g. "dashboard with dark mode") max_results: Number of results (default 15, max 100) include_pro: Include pro components (default True)

Inputs: project_description (required), max_results, include_pro. Returns: result

recommend_combinationA

Recommend a full-page component combination.

Given a project or page description, returns recommended components for each page section: navigation, hero, features, background, cards, CTA, footer, and text effects.

Args: description: Description of the page or project (e.g. "AI SaaS landing page") include_pro: Include pro components (default True)

Inputs: description (required), include_pro. Returns: result

recommend_componentsA

Recommend components for a specific use case or design goal.

Analyses the description against component metadata, categories, tags, and scoring dimensions to find the best matches.

Example descriptions:

  • "premium AI SaaS landing page with dark theme"

  • "subtle background effect for a login page"

  • "testimonial section for a marketing site"

  • "animated hero for a startup landing page"

Args: description: Free-text description of what you need max_results: Number of recommendations to return (default 10, max 100) include_pro: Include pro components (default True)

Inputs: description (required), max_results, include_pro. Returns: result

search_componentsA

Search components by text query with optional filters.

Searches across names, descriptions, tags, categories, purposes, behaviors, and visual characteristics. Results are ranked by relevance.

Args: query: Search query (e.g. "animated hero", "dark card") category: Optional category slug to narrow results tags: Optional comma-separated tags to filter by max_results: Max results to return (default 15, max 100) include_pro: Include pro components (default True)

Inputs: query (required), category, tags, max_results, +1 more. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4/5.0

    Scored across 12 tools

    Disambiguation3/5

    Several tools serve similar recommendation purposes (recommend_components, recommend_combination, match_components_to_project, generate_page_layout), which could confuse agents. However, descriptions clarify their distinct scopes (single recommendation, per-section, whole project, full layout). Other tools like filter_by_scores, search_components, and list_components are more distinct.

    Naming Consistency5/5

    All tools consistently use verb_noun naming with underscores (e.g., filter_by_scores, list_components, recommend_components). The pattern is predictable, even for longer names like match_components_to_project.

    Tool Count5/5

    12 tools is well-scoped for a UI component library server. It covers browsing, searching, filtering, recommending, installation, and monitoring without being excessive or too sparse.

    Completeness5/5

    The tool surface covers the full lifecycle of component discovery: listing, filtering, searching, retrieving details, installation instructions, and cache stats. No obvious gaps for the stated purpose of helping users find and use Aceternity components.

    Maintenance

    ActivityNo data
    ResponsivenessSyncing

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