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search_nodes

Read-onlyIdempotent

Find installed ComfyUI node classes by name, display name, or description. Narrow by category, and enable detail to view full input/output schemas in-line.

Instructions

Search node classes installed on the instance (name/display-name/description).

Use category to narrow (e.g. 'loaders', 'conditioning', 'sampling', 'ImpactPack'). Set detail=True to fold each hit's full input/output schema in-line (use a specific query + small limit) so you can skip the follow-up get_node_info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
detailNo
categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed5 schema fields changedv0.15.1
    • removedInput schema / properties / category / title
      Removed value: -"Category"
    • removedInput schema / properties / detail / title
      Removed value: -"Detail"
    • removedInput schema / properties / limit / title
      Removed value: -"Limit"
    • removedInput schema / properties / query / title
      Removed value: -"Query"
    • removedInput schema / title
      Removed value: -"search_nodesArguments"
  2. First observedv0.2.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only/idempotent/open world aspects. The description adds useful behavioral context: what fields are searched, how category narrows results, and that detail=True folds full I/O schema into each hit, letting the agent avoid a second call. No contradictions with the read-only/idempotent hints.

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 compact sentences front-load the core purpose and then give targeted usage and efficiency tips. Every clause adds value, no redundancy or filler. The structure is easy to parse for an agent: search, narrow, get details as needed.

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?

The description is complete for this read-only search tool given the output schema and annotations. It tells the agent what it searches, how to narrow with category, when to request detail, and how to avoid a follow-up get_node_info. Nothing essential for selecting or invoking this tool is missing.

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 carries the burden. It explains query semantics (search over name/display-name/description), category (narrow with examples), detail (in-line schema), and limit (small limit when using detail). It doesn't describe the bare 'limit' term, but that is semantically evident from the schema default.

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 and resource: 'Search node classes installed on the instance' with explicit match fields (name/display-name/description). It distinguishes itself from sibling tools by noting that setting detail=True lets you 'skip the follow-up get_node_info', and the word 'classes' separates it from search_node_packs.

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

Usage Guidelines4/5

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

Provides actionable guidance with concrete category examples ('loaders', 'conditioning', 'sampling', 'ImpactPack') and a rule for detail usage: set detail=True with a specific query and small limit to skip get_node_info. It clearly explains how to adjust behavior, though it doesn't enumerate when *not* to use this tool versus all possible siblings.

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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