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quasar-docs-mcp-server

by mamit514

quasar_get_component

Retrieve full documentation for any Quasar UI component, including API reference, props, events, slots, methods, and usage examples. Accepts component names with or without prefix.

Instructions

Get documentation for a specific Quasar UI component.

Returns the full markdown documentation including API reference, props, events, slots, methods, and usage examples.

Args:

  • component (string, required): Component name. Accepts various formats:

    • With prefix: 'q-btn', 'q-input', 'q-dialog'

    • Without prefix: 'btn', 'input', 'dialog'

    • Common aliases: 'button' -> 'btn', 'modal' -> 'dialog', 'dropdown' -> 'select'

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns: For markdown: Full component documentation with API details For JSON: { "component": string, // Original input "normalized_name": string, // Resolved component name "path": string, // File path in docs "url": string, // Quasar.dev URL "content": string, // Documentation content "truncated": boolean // Whether content was truncated }

Examples:

  • Get button docs: component="btn" or component="q-btn" or component="button"

  • Get dialog docs: component="dialog" or component="modal"

  • Get input docs: component="input" or component="textfield"

Errors:

  • Returns "Component not found" with suggestions if component doesn't exist

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
componentYesComponent name (e.g., 'btn', 'q-btn', 'input', 'q-input', 'dialog', 'button')
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
Behavior4/5

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

Discloses return formats (markdown and JSON), parameter behavior (aliases, normalization), and error responses. No side effects mentioned, but as a read-only getter, transparency is adequate given no 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?

Well-structured with sections (Args, Returns, Examples, Errors), front-loaded purpose, and no redundant sentences. Each part adds value.

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?

Covers purpose, parameters, return details, errors, and examples fully. Without an output schema, the description compensates by detailing both markdown and JSON structures.

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?

Adds significant value beyond schema: describes accepted formats (with/without prefix, aliases) and details JSON return structure. Schema coverage is 100%, so baseline is 3, but extra context raises score.

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?

Description clearly states 'Get documentation for a specific Quasar UI component' with a specific verb and resource. It differentiates from sibling tools like 'quasar_get_page' which retrieves page docs, making purpose distinct.

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

Usage Guidelines4/5

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

Provides explicit usage context with examples and error handling ('Returns Component not found with suggestions'). Does not explicitly exclude alternatives but implies focus on component retrieval.

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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