Skip to main content
Glama

ScanBIM MCP

by io.scanbimlabs

get_supported_formats

Return the full matrix of supported input formats organized by subscription tier (free / pro / enterprise). Use to tell a user whether their file type is accepted before calling upload_model, or to surface pricing tier info. When to use: you need to validate a file extension or show a customer the supported format list. When NOT to use: you already know the extension is common (.rvt/.ifc/.nwd/.obj) — just call upload_model, which returns an 'Unsupported format' error for anything outside the matrix. APS scopes: none (static data). 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 (not applicable: no APS call); 403 scope or resource permission denied (not applicable); 404 not applicable; 429 rate limited — backoff and retry (worker-level only); 5xx APS upstream outage — retry with jitter (not applicable). Side effects: READ-ONLY and pure. Idempotent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description discloses that the tool is READ-ONLY, pure, idempotent, and requires no APS scope. It also clarifies that many errors are not applicable. However, the rate-limit section includes irrelevant info about Model Derivative and OSS uploads, slightly detracting from clarity.

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

Conciseness3/5

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

The description is well-structured with clear headers, but there is redundancy between the introductory sentence and the 'When to use' section. The rate and error details are verbose and partially irrelevant, making it not as concise as it could be.

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 lacking an output schema, the description specifies the return value ('full matrix of supported input formats'), use cases, exclusions, safety profile, and error behavior. No further information is needed for correct invocation.

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?

There are zero parameters, so the description has no parameter semantics to add. The schema is empty and fully covers parameters, so the baseline 4 applies.

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 first sentence clearly defines the tool: 'Return the full matrix of supported input formats organized by subscription tier.' It specifies a concrete verb and resource, and distinguishes itself from siblings by explicitly tying to upload_model use cases.

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 includes explicit 'When to use' and 'When NOT to use' sections, naming upload_model as the alternative when the extension is common. This is exactly the guidance needed for tool selection.

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

All ScanBIM MCP 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

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