mcp-server-brewfather

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get_readings

Fetch hydrometer sensor readings for a batch, newest last, with an optional limit to avoid thousands of fermentation points. Returns total count plus time, specific gravity, and temperature in °C.

Instructions

Read a batch's sensor readings (hydrometer, e.g. Tilt/iSpindel), newest last.

Returns {total, readings: [{time, sg, temp, ...}]} with only the most recent
``limit`` readings (0 = all — can be thousands over a fermentation).
``total`` counts every reading the batch has. Temperatures are °C.

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": {
      "batch_id": "<batch_id>"
    },
    "name": "get_readings"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`batch_id`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.3.0Oct 4, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "title": "get_readingsDictOutput",
+  "type": "object"
+}

First observedv0.1.0Sep 28, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does a good job: it discloses ordering ('newest last'), the limit semantics including the 0 = all edge case, the potential scale ('can be thousands'), and units (°C). It does not cover auth/permission needs or error behavior for an unknown batch_id, which keeps it from a 5.

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?

Three short sentences, front-loaded with the core purpose, then return shape, then the limit caveat. Every sentence adds information an agent needs; nothing is filler.

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 2-param read tool with an output schema, this is close to complete: the output schema means return values needn't be explained, yet the description helpfully summarizes them anyway. The only real gap is the absence of any error/permission note for an invalid batch_id.

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 description coverage is 0%, so the description must compensate, and it does for limit (0 = all, most recent N) — well beyond the bare default of 20 in the schema. batch_id is left implicit, but its meaning is unambiguous from the tool name and purpose.

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?

States a specific verb+resource ('Read a batch's sensor readings') and narrows it with the device examples (Tilt/iSpindel), which cleanly separates it from sibling tools like get_batch, get_brewtracker, and list_inventory.

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?

Usage is implied — read hydrometer time-series for a given batch — but the description never says when to prefer this over get_batch or get_brewtracker, nor any prerequisite such as the batch needing a linked sensor. No explicit when/when-not guidance.

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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