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LogicMonitor MCP Server

get_datasource

Read-only

Fetch detailed datasource configuration including collection method, datapoints, thresholds, and appliesTo logic. Understand what it monitors and diagnose issues.

Instructions

Get detailed information about a specific datasource by its ID in LogicMonitor (LM) monitoring.

Returns: Complete datasource details: name, displayName, description, appliesTo logic, collection method, datapoints (metrics), thresholds, alert rules, polling interval.

When to use:

  • Understand what datasource monitors

  • Review alert thresholds

  • See collection method (SNMP/WMI/API/script)

  • Check datapoint definitions

  • Troubleshoot why datasource applies/doesn't apply to device

Key information returned:

  • appliesTo: Logic determining which resource/device get this datasource (e.g., "system.hostname =~"*prod*"")

  • dataSourceType: Collection method (SNMP, WMI, JDBC, API, script)

  • dataPoints: List of metrics collected (e.g., CPUBusyPercent, MemoryUsedPercent)

  • alertExpr: Threshold formulas (when to alert)

  • collectInterval: How often data is collected (seconds)

Understanding appliesTo logic: Shows why datasource does/doesn't monitor certain resources/devices. Common patterns:

  • isWindows() - Only Windows resource/device

  • system.devicetype == "server" - Only servers

  • hasCategory("AWS/EC2") - Only AWS EC2 instances

Workflow: Use "list_datasources" to find dataSourceId, then use this tool to understand how it works.

Related tools: "list_datasources" (find datasource), "list_resource_datasources" (see which resource/device use it).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataSourceIdYesThe ID of the datasource to retrieve
fieldsNoComma-separated list of fields to include in response. Examples: "id,displayName,hostStatus" or use "*" for all fields. Omit this parameter to receive a curated set of commonly used fields.
Behavior4/5

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

Annotations already indicate readOnlyHint=true; description adds detailed return field descriptions and explains appliesTo logic, providing behavioral context beyond annotations without contradiction.

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?

Well-structured with clear sections (summary, returns, when to use, key info, workflow). Slightly lengthy but every section adds value. Front-loaded with purpose.

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?

No output schema, but description thoroughly explains returned fields (appliesTo, dataSourceType, datapoints, etc.) and gives examples. Adequate for understanding tool output and usage context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema covers both parameters with full descriptions (100% coverage). Description does not add additional parameter semantics; it mentions key returned fields but not parameter usage details.

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?

Clearly states 'Get detailed information about a specific datasource by its ID' with distinct resource and action. Among sibling get_ tools, this purpose is unique and unambiguous.

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?

Includes a dedicated 'When to use' section listing specific scenarios (review thresholds, understand appliesTo, etc.). Also provides workflow suggestion to use list_datasources first and relates to sibling tools.

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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