Skip to main content
Glama
robert-mcdermott

Generative UI MCP Server

Generate Prefab Ui

generate_prefab_ui

Execute Prefab Python code in a sandbox to render interactive UI components. Build dynamic interfaces with reactive state, charts, and layout patterns.

Instructions

Execute Prefab Python code in a sandbox and render the result.

The code runs in a Pyodide WASM sandbox with full Python support. Import everything you use. Use the components tool to look up available components and their import paths.

Always use PrefabApp as the outermost context manager — this enables streaming so the UI renders progressively as code is written:

from prefab_ui.components import Column, Heading, Text, Row, Badge
from prefab_ui.app import PrefabApp

with PrefabApp() as app:
    with Column(gap=4):
        Heading("Dashboard")
        with Row(gap=2):
            Text("Revenue: $1.2M")
            Badge("On Track", variant="success")

For interactive UIs, pass initial state as a dict and use .rx on stateful components for reactive bindings:

from prefab_ui.components import Column, Slider, Text
from prefab_ui.app import PrefabApp

with PrefabApp(state={"threshold": 50}) as app:
    with Column(gap=4):
        slider = Slider(value=50, min=0, max=100, name="threshold")
        Text(f"Threshold: {slider.rx}%")

slider.rx produces {{ threshold }}, a template expression that resolves against client-side state. Use Rx("key") directly, or apply pipe filters: Rx("balance").currency() produces {{ balance | currency }}.

Available pipes: upper, lower, currency, length, json, round(n), default(val), truncate(n).

Charts live in prefab_ui.components.charts:

from prefab_ui.components.charts import BarChart, ChartSeries

BarChart(
    data=[{"month": "Jan", "rev": 100}, {"month": "Feb", "rev": 200}],
    series=[ChartSeries(data_key="rev", label="Revenue")],
    x_axis="month",
)

Values passed via data are available as global variables in the code. Python features like loops, f-strings, and comprehensions all work.

Layout patterns:

  • Card sub-components (CardHeader, CardContent, CardFooter) have built-in padding. Don't add extra padding to them. For a simple card without sub-components, use Card(css_class="p-6").

  • Use Grid(columns=N, gap=4) for equal-width cards or panels. Grid handles sizing automatically — no flex classes needed. For unequal widths, pass a list: Grid(columns=[2, 1], gap=4) gives a 2:1 ratio.

  • Row is for inline elements (badges, icons + text, buttons). Prefer Grid when children should have equal or proportional widths. Row does not wrap by default.

  • Column and Row accept gap (Tailwind scale: 1-12), align (cross-axis), and justify (main-axis) as native props — prefer these over raw css_class for spacing.

  • Use css_class="overflow-hidden" on containers if chart or content edges should clip to the container boundary.

Args: code: Python code that builds a Prefab component tree. data: Values injected as variables in the sandbox namespace. sandbox: A Sandbox instance. If not provided, a new one is created on each call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
dataNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so thoroughly. It discloses Pyodide WASM sandboxing, streaming behavior, reactive state mechanics, data injection as globals, and per-call sandbox creation.

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

Conciseness4/5

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

The description is long but well-structured: purpose, code examples, state handling, charts, layout patterns, then args. Each code sample earns its place for a code-generation tool, and the core instruction is front-loaded.

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

Completeness4/5

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

It covers setup, state, pipes, charts, and layout guidance, which is unusually complete for a two-parameter tool. The lack of an output schema is acceptable since the output is a rendered UI, but the phantom 'sandbox' parameter and lack of explicit error/return behavior keep it from a perfect score.

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

Parameters4/5

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

Schema coverage is 0%, and the description compensates by explaining 'code' as building a Prefab component tree and 'data' as injected sandbox variables, reinforced by extensive examples. However, it documents a 'sandbox' argument that does not appear in the input schema, which could mislead an agent into passing an unsupported parameter.

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 opening sentence states a specific action and resource: 'Execute Prefab Python code in a sandbox and render the result.' This clearly distinguishes the tool from the sibling search_prefab_components, which is for lookup rather than execution/rendering.

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?

The description gives concrete conditions: use the components tool for lookups, wrap with PrefabApp for streaming, use .rx for interactive UIs, and choose Grid vs Row based on layout needs. It does not explicitly contrast with sibling search_prefab_components, but the tool's role is evident from context.

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

Deploy Server

Other Tools