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Glama

The Quiet Protocol Growth Offense MCP

Scan AI Visibility

scan_ai_visibility
Read-only

Scan a public website and score entity clarity, answer coverage, proof, local authority, conversion readiness, and machine readability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesPrimary city or market.
nicheYesBusiness niche or vertical.
websiteUrlYesHomepage URL to scan.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYes
toolIdYes
fastWinsYes
findingsYes
scoreBandYes
subScoresNo
bookingCtaNo
engineSlugYes
limitationsYes
methodologyYes
nextStepUrlYes
canonicalUrlYes
evidenceTypeYes
overallScoreYes
scannedPagesNo
rubricVersionYes
systemMappingYes
inputAssumptionsYes
canonicalPublicUrlYes
evidenceReferencesYes
recommendedResourcesNo
evidenceClassificationYes

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds the clarification 'public website', which reinforces the openWorldHint but does not go further to describe outcomes like output structure or potential network dependencies. It neither contradicts nor enriches the annotations meaningfully, so a 3 is appropriate.

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?

A single, front-loaded sentence that immediately states the action and scope, then lists the output dimensions. Every word contributes to clarity, with no filler or redundant phrasing.

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?

The tool is a read-only scanner with a clear input set and an output schema (indicated by the context signals). The description sufficiently communicates the purpose and the dimensions evaluated, and the annotations cover safety. While it does not explicitly mention the output shape, the presence of an output schema means the description does not need to, making this adequate.

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?

The input schema covers all three parameters (websiteUrl, niche, city) with descriptions, and the description does not add any parameter-specific details beyond what is already in the schema. Since schema coverage is 100%, the baseline is 3; the description adds no extra semantic value for parameters.

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 verb 'Scan' with a specific resource ('public website') and enumerates the six dimensions it scores. It stands apart from the sibling tools, which are mostly get_* or run_* operations with different focuses, leaving no ambiguity about what this tool does.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus the many sibling scanning tools like run_competitor_intake_scanner or run_front_door_benchmark. It does not mention any conditions, exclusions, or alternatives, leaving the agent to infer usage from the name alone.

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

A3.5/5.0
Disambiguation4/5

Most tools have distinct purposes, with clear get/list/run patterns separating fetching, listing, and executing. A few tools like scan_ai_visibility and run_trust_stack_audit both scan websites but focus on different signals, so minor overlap exists but descriptions clarify boundaries.

Naming Consistency5/5

All 29 tools consistently use snake_case with verb_noun structure (get_, list_, run_, scan_, select_, find_, pricing_lookup). The naming convention is uniform and predictable, making it easy to infer tool behavior.

Tool Count2/5

With 29 tools, the server exceeds the typical comfortable range (16-25 is already heavy). While the domain is broad, the high count may overwhelm agents and increase selection complexity without clear benefit.

Completeness4/5

The server covers a comprehensive range of operations: listing, fetching, running diagnostics, scanning, and recommendations. It lacks CRUD operations, but as a read-only resource and diagnostic server, that's appropriate. Some minor gaps exist, but the core workflows are well covered.

Resources