Skip to main content
Glama

KrystalView Analytics

Get Browser Errors

get_errors
Read-onlyIdempotent

Get aggregated browser errors grouped by type and message, with affected paths and sample sessions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results to return.
error_typeNoFilter by error type.
unresolved_onlyNoOnly include unresolved errors.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesAggregated browser error groups with affected paths, counts, and sample sessions.
metaYesSite and rate-limit metadata for the current MCP call.

Schema Changelog

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

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral context about aggregation and output structure, but does not reveal additional behaviors (e.g., error handling, pagination). It adds moderate value beyond annotations.

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 a single, front-loaded sentence with no unnecessary words. Every phrase ('aggregated', 'grouped by type and message', 'affected paths and sample sessions') adds value, making it highly concise.

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 low complexity (3 optional parameters, no nested objects, and an existing output schema), the description adequately covers the tool's behavior. It explains the output structure, which compensates for any lack of detail in the output schema not shown. Annotations further support completeness.

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% for all 3 parameters, so the schema already documents each parameter's meaning. The description does not add further parameter details, earning a baseline score of 3.

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 uses specific verb 'Get' and resource 'browser errors', and details aggregation ('grouped by type and message') and output components ('affected paths and sample sessions'). This clearly distinguishes it from sibling tools like get_anomalies or get_campaign_roas.

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?

No guidance is provided on when to use this tool versus its many siblings (e.g., get_anomalies, get_sessions). There are no context cues, exclusions, or alternative suggestions, leaving the agent to infer usage without support.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation5/5

Each tool targets a distinct analytics dimension (anomalies, campaigns, errors, funnels, live visitors, notifications, scroll depth, sessions, site stats) with clear boundaries. Even overlapping concepts (sessions list vs detail vs live) are separated by distinct functionality.

Naming Consistency5/5

All tool names follow the consistent 'get_<resource>' pattern in snake_case, making it predictable for an agent to infer the purpose of each tool from the name alone.

Tool Count5/5

13 tools is well-scoped for an analytics server covering site stats, sessions, funnels, campaigns, errors, and real-time data. Each tool earns its place without redundancy or unnecessary complexity.

Completeness4/5

The set covers the major analytics domains (traffic, engagement, campaigns, errors, funnels, real-time). Minor gaps exist, such as missing tools for goal/conversion tracking beyond funnels, but core workflows are well supported.