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mcp-server-brewfather

by cacack
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

update_batch

Change a brewing batch's status or record measured values such as gravity, volume, pH, and temperature in BrewFather. Use it to keep batch progress and readings current.

Instructions

Update a batch's status and/or measured values.

``status``: Planning, Brewing, Fermenting, Conditioning, Completed, Archived.
``measurements`` keys (metric only — gravities SG, volumes liters, temps °C):
measuredMashPh, measuredBoilSize, measuredFirstWortGravity,
measuredPreBoilGravity, measuredPostBoilGravity, measuredKettleSize,
measuredOg, measuredFermenterTopUp, measuredBatchSize, measuredFg,
measuredBottlingSize, carbonationTemp. Returns {batch_id, result}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNo
batch_idYes
measurementsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It usefully discloses the return shape ({batch_id, result}) and the units expected for measurements, but says nothing about whether omitted fields are preserved (partial vs full update), permission requirements, or error behavior for a mutation tool.

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

Conciseness4/5

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

Front-loaded with the core action, then two clearly-labelled blocks for status and measurements. The measurement list is long but every entry is necessary because the schema does not enumerate it.

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 mutation tool with no annotations and no output schema, the description covers parameters well and gives a return shape. It still leaves partial-update semantics, permissions, and error conditions unaddressed for what is a write operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the schema types are generic (bare string for status, untyped number map for measurements), so the description's value is high: it supplies the full allowed status enum and the exact measurement key names with their metric units. This fully compensates for the schema gap.

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?

States a specific verb+resource ('Update a batch') and names exactly what can be changed (status and/or measured values). An agent can distinguish it from update_recipe or set_inventory, though the description never explicitly contrasts them.

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?

There is no statement of when to use this tool versus get_batch, find_batches, or update_recipe, and no prerequisites or exclusions. The enumeration of status values and measurement keys aids invocation but not tool selection.

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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