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lumics-mcp

Get component definitions

lumics_get_device_definition_components
Read-onlyIdempotent

Retrieve platform-wide component definitions to learn what fields each component type includes and how it is defined. Use this tool to interpret unfamiliar components by viewing their schema, file path, and management settings.

Instructions

Return the platform-wide component definitions that describe what each component type looks like: filePath, and a "data" block with modelName, itemType, componentAlias, isDefaultMonitored, nameProperty, the field "schema" (which property names a component of that type carries, and their types), and componentManagement. Use this when you need to know what fields a component type has or how it is defined — for instance to interpret an unfamiliar component. Its "schema" is the INVENTORY schema and carries no metric property names, so do NOT use it to find values for a metric tool's "properties" argument: a live contract run on 2026-07-30 grepped the whole payload and found zero occurrences of any metric type group. Use lumics_get_metric_summary for that instead (spec section 12.5 M6). This endpoint IS the source for a metric itemType, which is built as the filePath module/group path plus "data.itemType" joined by "_" — for example /components/snmp/common/Cpu.yml with itemType "cpu" gives "snmp_common_cpu". This is Lumics platform metadata, not tenant data: it is the same for every company, describes every type the product supports rather than the types this tenant uses, and takes no company id. It is also large, and it accepts no limit — if you only need a valid component type key for this tenant, call lumics_list_component_types instead, which is much smaller. Pass "fields" (e.g. ["filePath"]) to keep the response manageable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoOptional list of top-level field names to keep in the output, e.g. ["id","name","ipAddress","enabled"]. Use this on large lists to stay inside the output budget; omit it to see every field.
Behavior5/5

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

Even though annotations already declare readOnlyHint=true and destructiveHint=false, the description adds substantial behavioral context: the payload is large, accepts no limit, is platform-wide (same for every company), takes no company id, and its schema is the inventory schema with no metric property names. No contradictions exist.

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 long but every sentence carries meaningful information: purpose, structural details, usage warnings, alternative tool suggestions, and a derived itemType example. It is front-loaded with the primary purpose and flows logically.

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?

With no output schema, the description fully explains the returned structure (filePath, data block, schema field), the itemType composition rule (filePath + data.itemType), the platform-wide scope, and the large size/no-limit caveat. It also provides alternative tool recommendations. This is highly complete for a read-only metadata tool.

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?

The input schema already provides a full description of the 'fields' parameter (100% coverage). The description adds practical guidance with a concrete example ('fields' e.g. ['filePath']) and explains why to use it (to keep the response manageable). This goes beyond the schema baseline.

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 explicitly states 'Return the platform-wide component definitions' and describes the exact structure (filePath, data block with fields like modelName, itemType, etc.). It clearly distinguishes this tool from siblings like lumics_get_me and from similar tools like lumics_get_metric_summary and lumics_list_component_types.

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 gives explicit use cases: 'Use this when you need to know what fields a component type has or how it is defined.' It also provides clear exclusions and alternatives, such as 'do NOT use it to find values for a metric tool's properties argument' (use lumics_get_metric_summary) and 'if you only need a valid component type key for this tenant, call lumics_list_component_types instead.'

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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