Skip to main content
Glama

Search appCN components

search_components

Search for appCN components by describing your intent or using keywords. Returns ranked matches with details to help you pick the best one.

Instructions

Find appCN components by intent or keyword — e.g. 'chat input', 'voice indicator', 'streaming message', 'reasoning'. Returns ranked matches with their delight detail. Use get_component on the best match for the full source and docs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesWhat you're looking for, in plain words (intent or keywords).
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It states that the tool returns 'ranked matches with their delight detail,' implying a safe read operation. However, it does not disclose any potential limitations like result count, pagination, or response structure. A bit more detail on behavior would be beneficial.

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 two sentences that front-load the core purpose with examples. Every sentence adds value: the first defines the action and scope, the second provides workflow guidance. No wasted words.

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?

Given that the tool has a single required parameter and no output schema, the description is complete. It explains the input (intent/keywords), output (ranked matches with delight detail), and next step (use get_component). It lacks mention of result limits or sorting, but overall it's sufficient for agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'query' is fully described in the schema. The description adds value by providing example intents/keywords ('chat input', 'voice indicator'), which helps the agent formulate proper queries. Schema coverage is 100%, and the examples enrich meaning beyond the schema.

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 tool's function: 'Find appCN components by intent or keyword' with concrete examples ('chat input', 'voice indicator'). It explicitly differentiates from sibling tool 'get_component' by directing the agent to use that for full source/docs.

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 provides explicit guidance: 'Use get_component on the best match for the full source and docs.' This tells the agent exactly when to use this tool versus the sibling, showing the workflow.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Salah-XD/appCN'

If you have feedback or need assistance with the MCP directory API, please join our Discord server