mcp-server-brewfather

Overview Schema Source Related Servers Discussions Admin

create_recipe

Create a new Brewfather recipe by specifying type, fields, and ingredients so Brewfather can compute stats; returns the recipe ID.

Instructions

Create a new recipe.

``type`` is All Grain or Extract. ``fields`` takes the same settings as
update_recipe (author, notes, batchSize, boilSize, boilTime, efficiency).
``ingredients`` is a list of new items in update_recipe's add form (``kind``,
name, amount, … — no index). So Brewfather can compute stats, give
fermentables color and potential (SG, e.g. 1.037), hops alpha, use and time,
and yeasts attenuation.

Returns {recipe_id, note}; stats stay empty until the recipe is opened in
the Brewfather app.

Input Schema

TableJSON Schema

Name	Required	Default
`name`	Yes
`type`	No	All Grain
`fields`	No
`ingredients`	No

Output Schema

TableJSON 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": "create_recipeDictOutput",
+  "type": "object"
+}

Addedv0.1.1Oct 3, 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 well: it discloses the return shape {recipe_id, note} and the non-obvious post-condition that stats stay empty until the recipe is opened in the Brewfather app. It omits auth requirements and error/duplicate handling, but the key behavioral caveat is present.

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 structured detail on each parameter and the return/caveat. Dense but every sentence earns its place; the trailing stat-computation sentence is slightly long but justifies its length with concrete formats.

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 4-param mutation tool with no annotations, the description covers parameter formats, return value, and the stats caveat, which is what an agent needs. Only auth/permission context and failure modes are missing, and an output schema exists to cover return details.

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 is loosely typed (additionalProperties), so the description does the heavy lifting: it gives the `type` enum values (All Grain or Extract), lists the `fields` keys, and specifies ingredient structure including the critical 'no index' note. This adds meaning far beyond the schema.

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 opening sentence states a specific verb and resource ('Create a new recipe'), which cleanly separates it from update_recipe, get_recipe, and find_recipes in the sibling list. An agent can identify the operation without opening the schema.

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?

Creation is implied by the verb, and the description references update_recipe for field formats, but it never states when to create vs. modify an existing recipe or any prerequisites. Usage is inferable rather than explicit.

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

Deploy Server