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sylvia-iot-mcp

sylvia-iot-mcp

by woofdogtw
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

application_stats

Monitor IoT application message queues by retrieving uldata, dldataResp, and dldataResult statistics for a given application ID.

Instructions

Get queue statistics for an application (uldata, dldataResp, dldataResult queues).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "applicationId": "<applicationId>"
    },
    "name": "application_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault
applicationIdYesThe application ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

There are no annotations, so the description carries the full burden. 'Get' and 'statistics' imply a read-only inspection operation, and naming the queues adds scope context. However, it does not explicitly state that the tool has no side effects, what metrics are returned, or whether authentication or other preconditions apply.

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, front-loaded sentence with no filler. It conveys the action, target, and queue scope efficiently.

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?

For a one-parameter tool with full schema coverage, the description is minimally sufficient for an agent to identify and invoke it. However, there is no output schema and the description does not specify the shape or meaning of the returned statistics, leaving some ambiguity about what 'queue statistics' actually contains.

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?

The schema already fully documents the only parameter, applicationId, with 100% coverage. The description adds no parameter-level detail beyond what the schema provides, so the baseline score of 3 is appropriate.

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 states a specific verb ('Get'), a specific resource ('queue statistics'), and the target ('an application'), and explicitly names the three queues involved. This clearly differentiates it from sibling tools like network_stats and the various data_application_* list/count tools.

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 when to use the tool: when you need queue statistics for an application, specifically for uldata, dldataResp, and dldataResult queues. However, it does not explicitly contrast it with alternatives such as network_stats or data_application_* tools, nor does it state when not to use it.

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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