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list_apps

View all registered applications and their usage statistics for team management and monitoring.

Instructions

List all registered apps for the current team, with usage stats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler for the "list_apps" tool, which triggers an API request to /v1/apps.
    case "list_apps": {
      result = await apiRequest("GET", "/v1/apps");
      break;
    }
  • index.js:218-226 (registration)
    The definition and registration of the "list_apps" tool in the MCP tool list.
    {
      name: "list_apps",
      description:
        "List all registered apps for the current team, with usage stats.",
      inputSchema: {
        type: "object",
        properties: {},
      },
    },
Behavior2/5

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

With no annotations provided, the description carries full burden but only states it lists apps with usage stats. It doesn't disclose behavioral traits like pagination, rate limits, authentication needs, or what 'usage stats' entails (e.g., format, recency). This leaves significant gaps for a tool that likely returns data.

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 that front-loads the core action ('List all registered apps') and adds useful detail ('with usage stats'). There is no wasted text, making it highly concise and well-structured.

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 no annotations, no output schema, and a read operation with potential complexity (usage stats), the description is incomplete. It doesn't explain return values, error conditions, or behavioral constraints. For a tool that likely returns structured data, this leaves the agent under-informed.

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, and schema description coverage is 100% (empty schema). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for zero-parameter tools. No additional value is required beyond stating the purpose.

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 clearly states the verb ('List') and resource ('all registered apps for the current team'), with additional context about 'usage stats'. It distinguishes this from siblings like 'get_app' (singular) and 'get_active_users_all_apps' (users, not apps). However, it doesn't explicitly differentiate from all possible list operations, keeping it at 4 rather than 5.

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 versus alternatives. It doesn't mention prerequisites (e.g., team context), exclusions, or compare it to siblings like 'get_app' for single app details. Usage is implied by the purpose but not explicitly stated.

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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