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Glama

ScanBIM MCP

by io.scanbimlabs

xr_launch_ar_session

Create a shareable WebXR AR passthrough session URL and QR code. On phone or tablet with WebXR AR support, the model is overlaid on the camera feed at the requested scale. When to use: a field user needs to walk the jobsite with a phone and see the model overlaid in-place at 1:1 scale, or drop a tabletop mini-model on a desk. When NOT to use: the target device is a Meta Quest in VR mode — use xr_launch_vr_session. The device lacks WebXR AR (desktop browser) — use get_viewer_link. APS scopes: viewables:read data:read (enforced at viewer page load, not at tool call). 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 (only at viewer page load); 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 session_id (ar_). Inserts a row into D1 usage_log read by xr_list_sessions. No APS resources are created.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scaleNoModel placement scale. '1:1' for in-situ real-world scale, 'tabletop' for ~1:50 desk-top display, 'custom' to allow pinch-to-scale. Defaults to '1:1'.
model_idYesAPS URN (base64url-encoded, starts with 'dXJu', unpadded) of the model to load in AR.
session_nameNoHuman-readable session label shown in the session list.

Schema Changelog

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

  1. Changed6 schema fields changed
    • addedInput schema / properties / model_id / description
      Added value: +"APS URN (base64url-encoded, starts with 'dXJu', unpadded) of the model to load in AR."
    • addedInput schema / properties / model_id / examples
      Added value: +[
+  "dXJuOmFkc2sub2JqZWN0czpvcy5vYmplY3Q6c2NhbmJpbS1tb2RlbHMvMTcwMDAwMDAwMDAwMF9idWlsZGluZy5ydnQ"
+]
    • addedInput schema / properties / scale / description
      Added value: +"Model placement scale. '1:1' for in-situ real-world scale, 'tabletop' for ~1:50 desk-top display, 'custom' to allow pinch-to-scale. Defaults to '1:1'."
    • addedInput schema / properties / scale / examples
      Added value: +[
+  "1:1"
+]
    • addedInput schema / properties / session_name / description
      Added value: +"Human-readable session label shown in the session list."
    • addedInput schema / properties / session_name / examples
      Added value: +[
+  "Jobsite AR walkdown - 2026-04-18"
+]
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

No annotations are provided, so the description carries full burden. It discloses non-idempotency, session_id minting, D1 usage_log insertion, APS scope requirements, rate limits, and error handling. This is thorough behavioral disclosure beyond what annotations would typically provide.

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 long but extremely well structured, with labeled sections for purpose, usage, scopes, rate limits, errors, and side effects. It front-loads the main purpose in the first sentence and every section earns its place with actionable information.

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?

Despite no output schema, the description explains the tool's output (session URL and QR code) and thoroughly covers selection criteria, side effects, permissions, and error conditions. For a tool with this complexity, the description is highly complete.

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 each parameter already has a clear description with examples. The tool description itself adds no additional parameter semantics beyond what the schema already provides, so the 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 opens with a specific verb 'Create' and names the resource ('shareable WebXR AR passthrough session URL and QR code'). It clearly differentiates from sibling tools by explicitly stating when NOT to use it and directing to xr_launch_vr_session or get_viewer_link.

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?

Includes a dedicated 'When to use' section with two concrete scenarios (jobsite walkthrough, tabletop mini-model) and a 'When NOT to use' section naming exact alternative tools. This is exemplary usage guidance.

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.

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