Skip to main content
Glama

list_icon_providers_tool

Read-only

Discover available icon providers and their categories to understand the icon catalog structure for Ilograph diagrams.

Instructions

    Lists all available icon providers and their categories.

    This tool provides an overview of the icon catalog structure,
    showing available providers and their service categories.

    Returns:
        dict: Provider information with categories and icon counts
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The async handler function `list_icon_providers_tool` that fetches and returns icon provider information using the fetcher instance, with proper error handling and context logging.
    async def list_icon_providers_tool(ctx: Optional[Context] = None) -> Dict[str, Any]:
        """
        Lists all available icon providers and their categories.
    
        This tool provides an overview of the icon catalog structure,
        showing available providers and their service categories.
    
        Returns:
            dict: Provider information with categories and icon counts
        """
        try:
            if ctx:
                await ctx.info("Fetching icon provider information")
    
            # Get fetcher instance
            fetcher = get_fetcher()
    
            # Get provider information
            provider_info = await fetcher.get_icon_providers()
    
            if provider_info is None:
                error_msg = "Failed to fetch icon provider information. The service may be temporarily unavailable."
                if ctx:
                    await ctx.error(error_msg)
                return {"error": error_msg}
    
            if ctx:
                await ctx.info(
                    f"Retrieved information for {len(provider_info.get('providers', {}))} icon providers"
                )
            return provider_info
    
        except Exception as e:
            error_msg = f"Error fetching icon provider information: {str(e)}"
            if ctx:
                await ctx.error(error_msg)
            return {"error": error_msg}
  • The `@mcp.tool()` decorator registering `list_icon_providers_tool` with annotations for title, readOnlyHint, and description.
    @mcp.tool(
        annotations={
            "title": "List Available Icon Providers",
            "readOnlyHint": True,
            "description": "Lists all available icon providers and categories from the icon catalog",
        }
    )
  • Invocation of `register_fetch_icons_tool(mcp)` in the main server setup, which triggers the registration of the tool.
    register_fetch_icons_tool(mcp)
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds valuable context beyond annotations by specifying the return format ('dict: Provider information with categories and icon counts') and clarifying the scope ('overview of the icon catalog structure'), though it doesn't mention rate limits or authentication needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with three distinct paragraphs: purpose, context, and return value. Each sentence adds value without redundancy. It could be slightly more concise by combining the first two paragraphs, but overall it's efficient and front-loaded.

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 read-only, parameterless tool without an output schema, the description provides sufficient context: clear purpose, behavioral context about catalog structure, and explicit return format. It covers the essential aspects given the tool's simplicity and annotation support, though it doesn't detail error cases or example outputs.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose and output. This meets the baseline expectation for a parameterless tool.

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 specific action ('Lists all available icon providers and their categories') and resource ('icon providers'), distinguishing it from sibling tools like search_icons_tool. It provides a concrete verb+resource combination that leaves no ambiguity about what the 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 Guidelines3/5

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

The description implies usage context by mentioning 'overview of the icon catalog structure' and 'available providers and their service categories', suggesting this is for discovery purposes. However, it lacks explicit guidance on when to use this versus alternatives like search_icons_tool or any prerequisites/exclusions.

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/QuincyMillerDev/ilograph-mcp-server'

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