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MCP Server TypeScript Template

by minimind-org

example_operation

Process user data by validating and structuring inputs such as name, email, and date for integration with AI models in the MCP Server TypeScript Template.

Instructions

A simple example operation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYes
emailYes
nameYes

Implementation Reference

  • Core execution logic for the example_operation tool: builds a URL and sends an API request.
    export async function exampleApiCall(params: z.infer<typeof ExampleSchema>) {
      return sendRequest(buildUrl("https://example.com/search", params));
    }
  • index.ts:55-61 (handler)
    MCP CallToolRequest handler dispatching for example_operation: validates input with schema and invokes the core handler.
    case "example_operation": {
      const args = ExampleSchema.parse(request.params.arguments);
      const result = await operation.exampleApiCall(args);
      return {
        content: [{ type: "text", text: JSON.stringify(result, null, 2) }],
      };
    }
  • Zod schema defining the input parameters for the example_operation tool (name, email, date).
    export const ExampleSchema = z.object({
      name: z.string(),
      email: z.string(),
      date: z.string(),
    });
  • index.ts:34-38 (registration)
    Tool metadata registration in ListToolsResponse: name, description, and derived JSON input schema.
    {
      name: "example_operation",
      description: "A simple example operation",
      inputSchema: zodToJsonSchema(ExampleSchema),
    },
  • index.ts:11-11 (registration)
    Import of the operation module containing the tool handler.
    import * as operation from './operations/example-operation';
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. However, it offers no information about what the tool does (e.g., whether it's a read, write, or compute operation), its effects, permissions required, rate limits, or error handling. This leaves the agent with no insight into the tool's behavior beyond its name.

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

Conciseness3/5

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

The description is concise with a single sentence, but it is under-specified rather than efficiently informative. While it avoids unnecessary length, it does not front-load critical information, as the content is too vague to be helpful. It earns a baseline score for brevity but lacks substantive structure.

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

Completeness1/5

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

Given the tool's complexity (3 required parameters) and the absence of annotations and output schema, the description is completely inadequate. It does not explain the tool's purpose, usage, behavior, or parameters, leaving the agent with insufficient information to understand or invoke the tool correctly in any meaningful context.

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

Parameters1/5

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

The input schema has 3 required parameters (name, email, date) with 0% description coverage, meaning the schema provides no semantic details. The description does not mention any parameters or their purposes, failing to compensate for the schema's lack of information. This leaves all parameters undocumented and their roles unclear.

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

Purpose2/5

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

The description 'A simple example operation' is tautological, essentially restating the tool name 'example_operation' with minimal added meaning. It does not specify what the tool actually does (e.g., what action it performs or what resource it affects), nor does it differentiate from the sibling tool 'addition'. This leaves the purpose vague and uninformative.

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

Usage Guidelines1/5

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

The description provides no guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or comparisons to the sibling tool 'addition', making it impossible for an agent to determine appropriate usage scenarios. This lack of direction is misleading in practice.

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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