Mozaika

search_screens

Search real product UI screens for design reference.

Use this BEFORE designing any page/component so your output matches how the
best-designed products actually solve the problem. Returns structured metadata
(description, UX patterns, UI elements, colors, palette) plus an image_url.
Section/component/recipe hits also carry `measured` and `retina` booleans —
prefer measured:true, retina:true references (pixel-measured, high-res).

`query` alone works well — the filters below are optional. A value outside the lists is
treated as a HINT (it ranks, it does not exclude), and if the filters together match
nothing they relax rather than hand you an empty list. So a near-miss costs you nothing;
spelling one exactly is simply more precise.

Args:
    query: free text, e.g. "fintech onboarding", "dark dashboard", "Linear".
    page_type: one of Billing · Camera / Capture · Changelog · Chat / Assistant ·
        Checkout · Dashboard · Detail · Docs · Editor · Empty State · Feed ·
        Integrations · Landing Page · Log In · Map · Onboarding · Paywall · Player ·
        Pricing · Profile & Account · Search & Results · Settings · Sign Up · Stories.
    ux_pattern: e.g. "Dark Mode", "Filter & Sorting", "Stats / KPIs", "Data Table",
        "Command Palette", "Multi-step Form", "Sidebar Navigation", "Bento Grid",
        "Progressive Onboarding", "Empty State", "Kanban", "Master-Detail", "WYSIWYG".
    industry: one of AI · Analytics · Communication · Consumer · Creator · Data ·
        Design · Dev Tools · E-commerce · Entertainment · Fintech · Health & Fitness ·
        Productivity · Real Estate · Security · Travel & Local.
    platform: "Web", "iOS" or "Android" (mobile = official store-listing screens).
    limit: max results (1-40, default 12).
    kind: "page" (default, whole screens), "section" (page parts),
        "recipe" (live-decoded composed patterns: Command Palette, Navbar, Login,
        Data Table, Hero Effect...) or "component" (measured single components).
    section_type: narrows by type, e.g. kind="section" + "Pricing / Plans" /
        "Testimonial / Social Proof" / "Hero", or kind="recipe" + "Login" /
        "Navbar" / "Data Table" / "Hero Effect".

Input Schema

TableJSON Schema

Name	Required	Default
`kind`	No	page
`limit`	No
`query`	No
`industry`	No
`platform`	No
`page_type`	No
`ux_pattern`	No
`section_type`	No

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and succeeds: it explains that out-of-list filter values are treated as hints, that filters relax instead of returning empty lists, and that measured/retina results are preferable. This gives agents a realistic, actionable model of the tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and when-to-use, then proceeds into an easily scannable Args block. Despite its length, each sentence adds needed guidance for a tool with eight optional parameters and no schema descriptions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex eight-parameter search tool with no output schema and no annotations, the description is remarkably complete: every parameter is covered, defaults and boundaries are stated, return metadata is previewed, and edge-case behavior is explained. The agent can correctly select and invoke the tool without needing to inspect external references.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides zero description coverage, so the description compensates by richly documenting all eight parameters: query examples, page, industry, platform, kind, limit range, and section_type usage. The prose adds sem, listed values, and examples that the schema completely omits.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it searches real product UI screens for design reference, and it mentions what is returned (structured metadata plus image_url). This distinguishes it clearly from the get_screen/get_section/get_component-style siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit usage directive: 'Use this BEFORE designing any page/component so your output matches how the best-designed products actually solve the problem.' It does not explicitly name alternative sibling tools or say when not to use them, so it stops short of perfect exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Mozaika tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0

Disambiguation3/5

The compare_* / get_* / search_* family creates real overlap: compare_components, get_component, get_recipe, and search_screens(kind="component") can all answer similar component questions, and the drift family (get_design_drift, get_design_history, list_design_changes) requires careful reading to pick the right one. However, the detailed descriptions mostly draw clear lines between cross-product comparison, single-spec retrieval, and corpus-level search.

Naming Consistency4/5

The server mostly follows a clean verb_noun convention: get_*, compare_*, list_*, search_*, validate_design, generate_asset. The pattern is highly consistent, though a few names differ slightly in style (audit_code vs validate_design vs get_score), and pluralization varies in tools like compare_components and compare_sections.

Tool Count3/5

At 23 tools this is on the heavy side, and several calls overlap in scope enough to feel redundant. That said, the server's broad purpose suggests a design system reference plus audit platform, so the count is justifiable; it could be consolidated into a tighter 15-18 set.

Completeness4/5

The surface covers design system retrieval, component/section/recipe specs, screens and flows, search, audit/tools, icon assets, and drift/history of measured design tokens, leaving few cap gaps for the declared domain. Minor gaps remain around some metadata like direct screenshot banding by product, but no major dead-end workflow is apparent.

Resources

Need Help?