Nightscout MCP Server

get_glucose_history

Retrieve glucose readings for a specified period to review history, including sensor values, timestamps, and trend directions. Use lookback hours or date ranges to analyze patterns.

Instructions

Get glucose reading history for a specified time period. Returns SGV values with timestamps and trend directions. Use 'hours' for simple lookback or 'dateFrom'/'dateTo' for precise ranges.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_glucose_history"
  }
}

Input Schema

Name	Required	Description
`count`	No	Max number of entries to return (default: auto based on period)
`hours`	No	Number of hours to look back (1-168, default 24)
`dateTo`	No	End date (ISO 8601). Defaults to now.
`dateFrom`	No	Start date (ISO 8601). Overrides hours if set.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.4.0Sep 6, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose the return content (SGV values, timestamps, trend directions) and parameter precedence, which is helpful. However, it does not mention ordering, default count behavior, timezone handling, error cases, or access requirements, leaving some behavioral gaps.

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?

Two tight sentences with no filler. The core purpose and return value are front-loaded, and the parameter usage guidance is placed second. Every sentence contributes useful information.

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

Completeness4/5

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

For a simple read-only history tool with no output schema, the description covers the main invocation concerns: what data is returned and how to specify the time window. Minor gaps like default count and ordering do not prevent correct usage.

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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful selection guidance by framing 'hours' as a simple lookback and 'dateFrom'/'dateTo' as precise range control, which helps an agent choose the right parameter combination beyond what the schema states.

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 uses a specific verb ('Get'), names a concrete resource ('glucose reading history'), and specifies what is returned ('SGV values with timestamps and trend directions'). This clearly distinguishes it from siblings like get_current_glucose and glucose_at_time.

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 gives useful parameter-level guidance ('Use 'hours' for simple lookback or 'dateFrom'/'dateTo' for precise ranges'), but it does not explicitly contrast this tool with alternatives or state when not to use it. Usage context is implied by the tool name and description rather than made explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.