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get_nodes

Read-only

List nodes of a specific kind with optional attribute or relationship filters. Control pagination with offset and limit.

Instructions

List nodes of a specific kind — the default read path for typed queries with optional filtering and pagination.

Prefer this over query_graphql when you just need objects of one kind: results come back as display labels (fast, token-cheap) or full attribute dicts (include_attributes=True).

To discover available kinds, read the infrahub://schema resource. If your client does not support MCP resources, call the get_schema tool instead. To discover available filters for a kind, read infrahub://schema/{kind} or call get_schema(kind='...').

Filter keys follow the schema's filter map. Attribute filters use <attr>__value (e.g. {"name__value": "atl1"}) and relationship filters chain via <rel>__<attr>__value (e.g. {"site__name__value": "atl1"}). See infrahub://schema/{kind} for the full list of valid keys.

Use offset and limit to page through large result sets. The response always includes total_count and has_more so you know when to stop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesKind of the objects to retrieve. Check infrahub://schema for valid kinds.
branchNoBranch to query. Defaults to the default branch.
filtersNoAttribute/relationship filters. Keys follow the schema's filter map (e.g. {"name__value": "atl1"} or {"site__name__value": "atl1"}). See infrahub://schema/{kind} for the full filter map.
partial_matchNoUse partial (substring) matching for string filters.
include_attributesNoWhen True, return full attribute values in TOON tabular format instead of just display labels. More expensive — omit when you only need names/counts.
limitNoMaximum nodes to return. Default 50. Pass -1 for all results (caution: may be expensive).
offsetNoNumber of results to skip for pagination. Use with limit to page through results.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Beyond the readOnlyHint annotation, the description details output formats (display labels vs. full attributes), pagination metadata (total_count, has_more), and warns about expensive queries with limit=-1.

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 well-structured, starting with purpose, then usage, filters, and pagination. Every sentence is informative with no redundancy.

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?

Given the output schema exists, the description adequately covers all parameters and adds context for discovering kinds and filters, making it fully complete for effective use.

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?

Despite 100% schema coverage, the description adds significant value by explaining filter key patterns (e.g., name__value, rel__attr__value), include_attributes behavior, and pagination mechanics.

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 clearly states the tool lists nodes of a specific kind with filtering and pagination, and explicitly distinguishes it from query_graphql by noting when to prefer it.

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?

The description explicitly advises preferring this over query_graphql for single-kind queries, and references get_schema for discovering kinds and filters, providing clear when-to-use 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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