Skip to main content
Glama

nanoodle

by io.github.nanoodlecom

render-a-mockup

Describe a screen, keep the style guide: an LLM turns both into one dense image prompt and an image model renders the mockup. text×2 -> join -> llm -> image; returns image (qwen-image-3-pro) saved to disk (file path in result). Runs on NanoGPT — $0.20 deposit per call, paid in Nano (XNO) — settles at actual model cost + 20%, change returned; no account needed; last run $0.079, ~2m 16s.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
TextNodefault: "An underground dumpling cartel ops dashboard: live dumpling-shipment map across Taipei night markets, steam-timer hea..."; optional
Text_2NoText; default: "Style guide: premium, cinematic dark-mode product dashboard with an immediate wow factor, rendered as an exceptionall..."; optional
_payment_idNoPayment id from this tool's previous payment-required response. Phase 3 only: after /x402/watch closes with status paid, call again with the same arguments plus this id to open the RESULTS stream. Do not pass it while payment is still pending — monitor the watch SSE first.
System_promptNoSystem prompt; default: "You write image prompts for UI mockups. Given a screen description and a style guide, reply with ONE detailed image p..."; optional

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / Text / description
      Previous value: -"default: \"A habit-tracker web app dashboard: today's checklist, current streaks, a week-at-a-glance grid, and a quick-add button.\"; optional"New value: +"default: \"An underground dumpling cartel ops dashboard: live dumpling-shipment map across Taipei night markets, steam-timer hea...\"; optional"
  2. First observed

TDQS

A4.2/5.0
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 well: it discloses the Nano payment deposit/settlement model, approximate runtime, output format, and that the image is saved to disk with a file path returned. This gives concrete expectations beyond the schema.

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 two dense, front-loaded sentences: the first explains purpose and pipeline, the second packs relevant cost, payment, and runtime details. There is no filler, and the unusual Nano payment information earns its place.

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?

For a tool with no annotations and no output schema, the description covers invocation essentials: inputs, output location, model, cost, runtime, and no-account requirement. The two-phase _payment_id flow is hinted at via deposit language but mostly left to the schema, so one small completeness gap remains.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds some clarity by mapping the two text inputs to screen description and style guide, but it does not meaningfully elaborate on System_prompt or _payment_id beyond what the schema already provides.

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: a screen description and style guide are fused into one image prompt and rendered as a mockup by an image model. The pipeline notation (text×2 -> join -> llm -> image) and model name distinguish it from sibling image tools.

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

Usage Guidelines3/5

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

The usage is implied: provide a screen description and a style guide. However, it does not explicitly say when to choose this over sibling tools like night-market-postcard or combine-images, nor does it give exclusions or routing conditions.

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

All nanoodle toolsInspect
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

B3.4/5.0
Disambiguation3/5

Most tools target clearly different media or output types, but several image-generation tools are near-variants (alishan-fog-dawn vs. night-market-postcard; combine-images vs. edit-a-photo). The descriptions are specific enough to recover, but the name-level distinction is weak.

Naming Consistency3/5

All names share lowercase kebab-case, but the semantic pattern is mixed: some are verb phrases (combine-images, render-a-mockup), some are nouns (favicon, character-sprites), and some are opaque demo titles (alishan-fog-dawn, fibo-studio-still, deslop). Readable overall, but not predictable.

Tool Count4/5

At 14 tools the count is reasonable for a creative-media demo server and each major modality has at least one representative. Several tools are close variants of one another, so the set feels slightly padded rather than tightly scoped.

Completeness3/5

The set covers image, video, audio, text, avatar, sprite, and mockup generation, which is broad coverage. However, there is no generic text-to-image or arbitrary photo-editing tool, only themed demos, so general creative requests would hit gaps.

Resources