hydra-mcp

hydra_reference

Read-only

Check Hydra transform functions, their inputs, defaults, and types before use. Prevents errors by verifying function names in the running engine.

Instructions

Hydra's transform functions, read live from the running engine — so it lists exactly what this tab's hydra-synth has, including anything added with setFunction.

no arguments: names grouped by type, plus the primer (idioms and gotchas)
name="modulate": that function's inputs and defaults (also fuzzy: name="repeat")
type="combineCoord": every function of one type

Types, and what they chain onto: src start a chain: osc, noise, voronoi, shape, gradient, solid, src, prev coord move pixels: rotate, scale, repeat, kaleid, scroll… color change colour: color, brightness, contrast, hue, colorama, luma… combine mix another source in: add, blend, mult, diff, layer, mask combineCoord warp by another source: modulate, modulateScale, modulateRotate…

Check a name here before using one you are not sure of — an invented function is refused by the dry run anyway, but this is cheaper.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	No
`type`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 14, 2026

TDQS

A5/5.0

Behavior5/5

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

Beyond the readOnlyHint and destructiveHint annotations, the description discloses that the listing is read live from the running engine, includes setFunction additions, and supports fuzzy matching for name lookups. It also documents grouping behavior and the type taxonomy. No statement contradicts the annotations.

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?

The description is front-loaded with the core behavior and usage modes, then uses compact bullets for the type taxonomy and closes with a practical precaution. Despite its length, every line contributes a distinct fact or example and avoids filler.

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

Completeness5/5

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

For a two-optional-parameter read-only reference with an output schema, the description covers invocation modes, parameter semantics, valid type values, and example queries. It even warns about the consequence of an invented function. Nothing material is missing for an agent to call it correctly.

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%, but the description fully compensates: it defines name as a function lookup returning inputs and defaults, notes fuzzy matching, and defines type as a filter returning every function of one type, enumerating the valid type values. This is far more useful than the bare string properties in 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 description opens with a concrete verb and resource: it reads Hydra's transform functions live from the running engine and lists them, making it a lookup tool rather than a mutation tool. The title annotation 'Look Up A Function' and the modal breakdown (no arguments, name, type) further distinguish it from sibling tools like hydra_define or hydra_drop.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says to check a name here before using an unverified function and contrasts this with the dry run, calling it 'cheaper'. The bullet list gives clear when-to-use modes for no arguments, name, and type. This gives an agent both the condition and the comparison needed to select the tool.

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