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search_icons

Find vector icons across multiple collections with typo-tolerant full-text search, then filter results by category or icon pack to quickly locate the right asset.

Instructions

Search 322,000+ vector icons across all collections (Lucide, Heroicons, Phosphor, Tabler, Material, etc.) using typo-tolerant full-text search.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_icons"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of icons to return (1-50, default is 10).
queryYesKeyword or term to search for (e.g. "shopping-cart", "chevron-right", "bell", "database", "github").
categoryNoOptional category filter (e.g. "arrows", "e-commerce", "finance", "communication").
collectionNoOptional collection pack filter (e.g. "lucide", "heroicons", "tabler", "phosphor", "simple-icons").

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the burden. It does disclose useful behavior: corpus size, cross-collection coverage, and typo-tolerant matching. It says nothing about result ordering/relevance ranking, pagination beyond the limit param, or that results are read-only lookups, which leaves real gaps for a search tool.

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 with zero filler: the scope (322k icons, all collections) comes before the search behavior. Nothing could be cut without losing information.

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?

For a simple four-parameter read tool with no annotations and no output schema, the description covers what it searches and how matching works. The only shortfall is that it doesn't hint what a result looks like (e.g. an icon identifier usable with get_icon), which matters for chaining.

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%, so every parameter is already documented with examples and defaults, establishing the baseline of 3. The description only echoes the collection names that the schema already lists as examples for the collection filter and adds no syntax or filtering semantics beyond that.

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?

States a specific verb plus resource: full-text search over 322,000+ vector icons across named collections, with the typo-tolerant characteristic called out. This clearly separates it from get_icon (single fetch) and list_collections (browsing packs) without needing the schema.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: mentioning collection names and typo tolerance signals 'discovery when you don't know the exact name.' It never says when NOT to use it (e.g. use get_icon once you have an exact name, or list_collections to browse) and gives no prerequisites.

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