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21st-dev

Magic Component Platform (MCP)

by 21st-dev

21st_magic_component_inspiration

Search 21st.dev for UI component inspiration and previews, returning JSON data of matching components to integrate into your codebase.

Instructions

"Use this tool when the user wants to see component, get inspiration, or /21st fetch data and previews from 21st.dev. This tool returns the JSON data of matching components without generating new code. This tool ONLY returns the text snippet for that UI component. After calling this tool, you must edit or add files to integrate the snippet into the codebase."

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesFull users message
searchQueryYesSearch query for 21st.dev (library for searching UI components) to find a UI component that matches the user's message. Must be a two-four words max or phrase

Implementation Reference

  • The async execute method implements the core tool logic: POSTs user message and search query to 21st.dev /api/fetch-ui endpoint, returns the UI component text as MCP content.
    async execute({ message, searchQuery }: z.infer<typeof this.schema>) {
      try {
        const { data } = await twentyFirstClient.post<FetchUiResponse>(
          "/api/fetch-ui",
          {
            message,
            searchQuery,
          }
        );
    
        return {
          content: [
            {
              type: "text" as const,
              text: data.text,
            },
          ],
        };
      } catch (error) {
        console.error("Error executing tool", error);
        throw error;
      }
    }
  • Zod schema for tool inputs: 'message' (full user message, string) and 'searchQuery' (2-4 word phrase for UI component search).
    schema = z.object({
      message: z.string().describe("Full users message"),
      searchQuery: z
        .string()
        .describe(
          "Search query for 21st.dev (library for searching UI components) to find a UI component that matches the user's message. Must be a two-four words max or phrase"
        ),
    });
  • src/index.ts:24-24 (registration)
    Instantiates and registers the FetchUiTool with the MCP server.
    new FetchUiTool().register(server);
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns JSON data and text snippets, and it adds context about post-call actions: 'After calling this tool, you must edit or add files to integrate the snippet into the codebase.' This gives useful behavioral insight into workflow integration. However, it lacks details on permissions, rate limits, or error handling, which are gaps for a tool with 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.

Conciseness4/5

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

The description is appropriately sized and front-loaded, starting with usage context. Every sentence adds value: the first states when to use it, the second specifies the return type and limitation, and the third adds post-call instructions. There's minimal waste, though it could be slightly more structured for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and 2 parameters with full schema coverage, the description is moderately complete. It covers purpose, usage, and post-call actions, but lacks details on return format (beyond 'JSON data' and 'text snippet'), error cases, or integration specifics. For a tool with siblings and no structured output, it should do more to compensate for these gaps.

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 the schema already documents both parameters ('message' and 'searchQuery'). The description doesn't add any meaning beyond what the schema provides—it doesn't explain how parameters interact or their practical use. With high schema coverage, the baseline is 3, and the description doesn't compensate with extra insights.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'returns the JSON data of matching components' and 'returns the text snippet for that UI component', which clarifies it fetches and returns component data. However, it doesn't clearly distinguish from sibling tools like '21st_magic_component_builder' or '21st_magic_component_refiner'—it mentions 'without generating new code' but doesn't specify how this differs from those siblings in purpose.

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?

The description provides clear context for when to use it: 'when the user wants to see component, get inspiration, or /21st fetch data and previews from 21st.dev'. It also implies an alternative by stating 'without generating new code', which hints at sibling tools that might generate code. However, it doesn't explicitly name alternatives or specify when not to use it, such as for editing or refining components.

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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