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ScanBIM MCP

by io.scanbimlabs

lumion_render

Queue a Lumion-style architectural visualization still render with landscaping, people, vehicles, and atmospheric effects. Returns a render_id and preview_url; the render pipeline is a ScanBIM roadmap item so today this tool responds synchronously with a stub job descriptor. When to use: you want a more 'Lumion-flavored' render (lush entourage, vehicles, people) vs. Twinmotion's cleaner look. When NOT to use: you need real-time viewing — use get_viewer_link. You need video — use twinmotion_walkthrough. APS scopes: none today (render pipeline is ScanBIM-internal); viewables:read data:read will apply when live. Rate limits: APS default ~50 req/min per app per endpoint; Model Derivative translation jobs ~60 req/min; OSS uploads size-limited per file to 100MB for direct upload, larger via resumable. Errors: 401 APS token expired/invalid — refresh (will apply when pipeline is live); 403 scope or resource permission denied; 404 URN not found — check the ID; 429 rate limited — backoff and retry; 5xx APS upstream outage — retry with jitter. Side effects: NON-IDEMPOTENT. Each call mints a new render_id (lum_). Inserts a row into D1 usage_log.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoOverall visual preset. 'photorealistic' = full PBR, 'artistic' = painterly, 'sketch' = line-drawing overlay, 'aerial' = drone perspective.
model_idYesAPS URN (base64url-encoded, starts with 'dXJu', unpadded) of the model to render.
add_peopleNoPopulate animated/static human entourage. Defaults to true.
add_vehiclesNoPopulate cars, trucks, and other vehicles in parking/streets. Defaults to false.
add_landscapingNoPopulate trees, shrubs, and ground cover appropriate to region. Defaults to true.

Schema Changelog

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

  1. Changed10 schema fields changed
    • addedInput schema / properties / add_landscaping / description
      Added value: +"Populate trees, shrubs, and ground cover appropriate to region. Defaults to true."
    • addedInput schema / properties / add_landscaping / examples
      Added value: +[
+  true
+]
    • addedInput schema / properties / add_people / description
      Added value: +"Populate animated/static human entourage. Defaults to true."
    • addedInput schema / properties / add_people / examples
      Added value: +[
+  true
+]
    • addedInput schema / properties / add_vehicles / description
      Added value: +"Populate cars, trucks, and other vehicles in parking/streets. Defaults to false."
    • addedInput schema / properties / add_vehicles / examples
      Added value: +[
+  false
+]
    • addedInput schema / properties / model_id / description
      Added value: +"APS URN (base64url-encoded, starts with 'dXJu', unpadded) of the model to render."
    • addedInput schema / properties / model_id / examples
      Added value: +[
+  "dXJuOmFkc2sub2JqZWN0czpvcy5vYmplY3Q6c2NhbmJpbS1tb2RlbHMvMTcwMDAwMDAwMDAwMF9idWlsZGluZy5ydnQ"
+]
    • addedInput schema / properties / style / description
      Added value: +"Overall visual preset. 'photorealistic' = full PBR, 'artistic' = painterly, 'sketch' = line-drawing overlay, 'aerial' = drone perspective."
    • addedInput schema / properties / style / examples
      Added value: +[
+  "photorealistic"
+]
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly covers side effects (non-idempotent, new render_id, D1 usage_log insert), the current stub behavior, APS scopes, rate limits, and error handling. This is far more transparent than typical tool descriptions.

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 well-structured with labeled sections (purpose, when to use, scopes, rate limits, errors, side effects) and is front-loaded with the core function. While it includes generic APS rate-limit and error details that add length, each section provides useful context with minimal waste.

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?

Given the tool's complexity (stub pipeline, non-idempotent behavior, no output schema), the description is thoroughly complete. It explains return values, side effects, error semantics, rate limits, and alternatives, making the tool fully actionable without additional external information.

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%, and the schema already includes detailed descriptions for all five parameters. The tool description mentions entourage and landscaping, which maps to booleans, but doesn't add new meaning beyond the schema definitions. Baseline of 3 is appropriate.

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 clearly states the tool's function: 'Queue a Lumion-style architectural visualization still render' and specifies the return values (render_id and preview_url). It distinguishes itself from sibling tools by explicitly comparing Lumion's lush entourage to Twinmotion's cleaner look.

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

Usage Guidelines5/5

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

The description provides explicit 'When to use' and 'When NOT to use' guidance, naming alternatives such as get_viewer_link for real-time viewing and twinmotion_walkthrough for video. This gives the agent clear decision criteria.

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

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TDQS

A4.4/5.0
Disambiguation4/5

Tools are grouped by domain with clear prefixes (acc_, xr_, get_) and each has a distinct purpose. The only potential confusion is between lumion_render and twinmotion_render, but descriptions clarify the aesthetic difference. Overall, tools are clearly differentiated.

Naming Consistency4/5

Most tools follow consistent patterns: acc_* for ACC operations, get_* for metadata retrieval, and xr_launch_*/xr_list_* for XR sessions. Minor deviations like list_models instead of get_models and render tools using software names as prefixes are readable and do not hinder pattern recognition.

Tool Count4/5

At 19 tools, the count is slightly above the ideal range but justified by the server's broad scope covering ACC, model translation, clash detection, rendering, and XR. Some render tools are stubs and could be trimmed, but they are clearly marked as roadmap items.

Completeness3/5

The set covers upload→translate→view→clash-detect→create issues/RFIs workflows well, but lacks update/delete operations for issues and RFIs, and there is no full-detail retrieval for a single issue or RFI. These gaps can cause workflow dead ends for closeout and status changes.

Resources