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LogicMonitor MCP Server

list_integrations

Read-only

List all third-party integrations configured in LogicMonitor, including Slack, PagerDuty, ServiceNow, and Jira, with status and configuration details.

Instructions

List all third-party integrations configured in LogicMonitor (LM) monitoring.

Returns: Array of integrations with: id, name, type (Slack/PagerDuty/ServiceNow/Jira/etc), status (active/inactive), configuration summary, authentication status.

What are integrations: Connections to external platforms for alert notifications, ticket creation, chat messages, incident management. Extend LogicMonitor alerting beyond email/SMS.

When to use:

  • Find integration IDs for escalation chains

  • Verify integrations are working

  • Audit external connections

  • Check authentication status

  • Review available integration options

Popular integrations:

Incident Management:

  • PagerDuty: Page on-call engineers for critical alerts

  • Opsgenie: Alternative incident management and on-call scheduling

  • VictorOps (Splunk On-Call): Alert routing and escalation

Ticketing:

  • ServiceNow: Auto-create incidents for alerts

  • Jira: Create tickets for infrastructure issues

  • Zendesk: Customer-facing service desk integration

Collaboration:

  • Slack: Post alerts to channels, interactive notifications

  • Microsoft Teams: Teams channel notifications

  • Mattermost: Self-hosted chat notifications

Workflow & Automation:

  • Webhooks: Custom integrations to any HTTP endpoint

  • API: Programmatic integration for custom workflows

Use cases:

  • "Post critical production alerts to #incidents Slack channel"

  • "Auto-create ServiceNow ticket for every critical alert"

  • "Page PagerDuty when datacenter resource/device go offline"

  • "Update Jira epic when deployment causes alerts"

Integration status:

  • Active: Integration configured and working

  • Inactive: Disabled or authentication failed

  • Test: Verify integration by triggering test notification

Workflow: Use this tool to find integrations, then use in escalation chains or as webhook recipients for alert delivery.

Important: A negative "total" value in the response indicates incomplete results. Use pagination (size/offset parameters) or set autoPaginate: true to retrieve all items.

Related tools: "get_integration" (configuration details), "test_integration" (verify working), "list_escalation_chains" (see usage).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoNumber of results per page (default: 50, max: 1000).
offsetNoStarting offset for pagination (default: 0). Use this to skip a specific number of results.
autoPaginateNoAutomatically fetch all pages (default: false). When true, fetches all results across multiple pages. When false, returns only the requested page. Use false for large result sets to avoid long response times.
filterNoFilter expression using LogicMonitor query syntax. Examples: name:*prod*, displayName~*server*, id>100, hostStatus:normal. Available operators: : (equals), ~ (includes), !: (not equals), !~ (not includes), >: (greater than or equals), <: (less than or equals), > (greater than), < (less than). Multiple conditions: Use comma (,) for AND, use || for OR. Do NOT use &&.
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.
Behavior5/5

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

Annotations only provide readOnlyHint: true, but the description adds significant behavioral details: a negative 'total' indicates incomplete results, pagination behavior (size/offset/autoPaginate), and integration status meanings (active/inactive/test). No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is verbose, including a lengthy 'Popular integrations' list and definitions of integrations that could be external documentation. It is front-loaded with purpose, but the extra content makes it longer than necessary for an AI agent.

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 tool is a read-only list with no required parameters and clear annotations, the description is complete: it explains the return array structure, pagination edge cases, filtering, status meanings, and related tools. No output schema needed.

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?

Schema coverage is 100%, so the baseline is 3. The description does not add meaningful semantics beyond the schema; the autoPaginate note is behavioral, not parameter-specific. Thus, no boost.

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 all third-party integrations in LogicMonitor, specifies what is returned (id, name, type, status, etc.), and distinguishes it from sibling tools like get_integration and test_integration.

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?

The description includes a 'When to use' section with five specific use cases and a 'Workflow' note, providing clear guidance on when to use this tool. It lacks explicit exclusions or when-not-to-use scenarios, but the context is comprehensive.

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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