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Xutaotaotao

mcp-get-installed-apps

get-installed-apps

Retrieve a list of installed applications on your computer using this tool, enabling quick access to software inventory and system details.

Instructions

Get my computer's installed apps

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'get-installed-apps' tool. It fetches the list of installed apps using getInstalledApps() and formats the result as JSON text in the MCP response format.
    async () => {
      const apps = await getInstalledApps();
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(apps, null, 2),
          },
        ],
      };
    }
  • src/index.ts:15-29 (registration)
    Registers the 'get-installed-apps' tool on the MCP server with its name, description, and handler function.
    server.tool(
      "get-installed-apps",
      "Get my computer's installed apps",
      async () => {
        const apps = await getInstalledApps();
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(apps, null, 2),
            },
          ],
        };
      }
    );
  • Imports the getInstalledApps utility function, which provides the core logic for retrieving installed applications and is called within the tool handler.
    import { getInstalledApps } from "get-installed-apps";
Behavior2/5

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. It mentions 'Get' which implies a read operation, but fails to describe critical traits like whether this requires permissions, what format the output is in, if it's paginated, or any rate limits. For a tool with zero annotation coverage, this is inadequate.

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 a single, efficient sentence with no wasted words. It is front-loaded with the core purpose, making it easy for an AI agent to quickly understand the tool's function without unnecessary elaboration.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It does not explain what the return values are (e.g., list format, data structure) or address behavioral aspects like permissions or errors. For a tool that retrieves system data, this leaves significant gaps in understanding.

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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the inputs. The description does not need to add parameter information, and it appropriately avoids redundancy. A baseline of 4 is applied since no parameters exist, and the description does not introduce confusion.

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

Purpose4/5

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

The description 'Get my computer's installed apps' clearly states the action (get) and resource (installed apps) with a specific scope (my computer). It's not tautological with the tool name 'get-installed-apps' and provides a meaningful purpose. However, without sibling tools, the differentiation aspect is not applicable, preventing a perfect score.

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

Usage Guidelines2/5

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, such as prerequisites, alternatives, or exclusions. It simply states what the tool does without context for usage, which is a significant gap in helping an AI agent make informed decisions.

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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