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Mi Fitness MCP CN

Mi Fitness MCP CN

by binglua
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

query_sleep

Retrieve sleep sessions from Xiaomi Mi Fitness data including start and end dates. Optionally include naps for complete sleep tracking.

Instructions

Query sleep sessions

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": {
      "start_date": "<start_date>",
      "end_date": "<end_date>"
    },
    "name": "query_sleep"
  }
}

Input Schema

NameRequiredDescriptionDefault
start_dateYes
end_dateYes
include_napsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.1/5.0
Behavior1/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but 'Query sleep sessions' only implies a read-only operation. It does not mention whether naps are included, how sessions are defined, what output is returned, or any side effects. This is insufficient for a tool with three parameters and no output schema.

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

Conciseness2/5

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

The description is a single short sentence, but it is under-specified rather than concise in a helpful way. It lacks essential detail, making it closer to a placeholder than an efficient explanation.

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 has three parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain how the tool behaves, what inputs are required, or what results to expect, making it inadequate for reliable tool selection and invocation.

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?

Schema description coverage is 0%, so the description must compensate by explaining the parameters. It provides no information about start_date, end_date, or include_naps, leaving the agent with no semantic meaning beyond raw schema names.

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 identifies the resource ('sleep sessions') and differentiates from sibling tools that query other metrics like heart rate or workouts. However, it lacks scope details (e.g., date range vs. all sessions, or whether it returns summaries or raw sessions), making it slightly less specific than an ideal purpose statement.

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?

No guidance is provided on when to use this tool versus alternatives. The name implies sleep-related queries, but there is no explicit context, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

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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