Prototipo · Versión preliminar: todos los servidores del registro oficial, sincronizados cada 30 minutos. Las reseñas y las cuentas llegarán en una etapa posterior.
PopNx MCPServidores MCP para quienes usan IA · explicados con palabras sencillas

Logicmonitor

de ryanmatversión 1.5.1i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.ryanmat/logicmonitor

Instalar

Resumen

Descripción del creador (original en inglés)

LogicMonitor API integration with 167 tools for alerts, devices, dashboards, and more.

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Otros
  • Debes completar: LM_PORTAL, LM_BEARER_TOKEN, LM_ACCESS_KEY

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

  • Revisiones básicas: 1 de 1 superadas
  • Se ejecuta en tu computadora con los permisos de tu usuario (archivos, red, apps).
  • Debes completar tú: LM_PORTAL, LM_BEARER_TOKEN, LM_ENABLE_WRITE_OPERATIONS, LM_ACCESS_ID, LM_ACCESS_KEY, LM_ENABLED_TOOLS, LM_DISABLED_TOOLS, LM_LOG_LEVEL

Los valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.

Necesitas

  • PyPIuv de Python instalado (para el comando uvx)

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

{
  "mcpServers": {
    "logicmonitor": {
      "command": "uvx",
      "args": [
        "lm-mcp"
      ],
      "env": {
        "LM_PORTAL": "your-value",
        "LM_BEARER_TOKEN": "your-value",
        "LM_ENABLE_WRITE_OPERATIONS": "your-value",
        "LM_ACCESS_ID": "your-value",
        "LM_ACCESS_KEY": "your-value",
        "LM_ENABLED_TOOLS": "your-value",
        "LM_DISABLED_TOOLS": "your-value",
        "LM_LOG_LEVEL": "your-value"
      }
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add logicmonitor --env LM_PORTAL=your-value --env LM_BEARER_TOKEN=your-value --env LM_ENABLE_WRITE_OPERATIONS=your-value --env LM_ACCESS_ID=your-value --env LM_ACCESS_KEY=your-value --env LM_ENABLED_TOOLS=your-value --env LM_DISABLED_TOOLS=your-value --env LM_LOG_LEVEL=your-value -- uvx lm-mcp

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

{
  "mcpServers": {
    "logicmonitor": {
      "command": "uvx",
      "args": [
        "lm-mcp"
      ],
      "env": {
        "LM_PORTAL": "your-value",
        "LM_BEARER_TOKEN": "your-value",
        "LM_ENABLE_WRITE_OPERATIONS": "your-value",
        "LM_ACCESS_ID": "your-value",
        "LM_ACCESS_KEY": "your-value",
        "LM_ENABLED_TOOLS": "your-value",
        "LM_DISABLED_TOOLS": "your-value",
        "LM_LOG_LEVEL": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "servers": {
    "logicmonitor": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "lm-mcp"
      ],
      "env": {
        "LM_PORTAL": "your-value",
        "LM_BEARER_TOKEN": "your-value",
        "LM_ENABLE_WRITE_OPERATIONS": "your-value",
        "LM_ACCESS_ID": "your-value",
        "LM_ACCESS_KEY": "your-value",
        "LM_ENABLED_TOOLS": "your-value",
        "LM_DISABLED_TOOLS": "your-value",
        "LM_LOG_LEVEL": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Valores que debes completar

  • LM_PORTAL obligatorio env
    LogicMonitor portal hostname (e.g., company.logicmonitor.com)
  • LM_BEARER_TOKEN secreto obligatorio env
    LogicMonitor API Bearer token
  • LM_ENABLE_WRITE_OPERATIONS env
    Enable write operations (create, update, delete)
  • LM_ACCESS_ID env
    LMv1 API access ID (required for log/metric ingestion)
  • LM_ACCESS_KEY secreto env
    LMv1 API access key (required for log/metric ingestion)
  • LM_ENABLED_TOOLS env
    Comma-separated tool names or glob patterns to enable (e.g., get_*,create_device)
  • LM_DISABLED_TOOLS env
    Comma-separated tool names or glob patterns to disable (e.g., delete_*)
  • LM_LOG_LEVEL env
    Logging level for API request debugging (debug, info, warning, error)

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub ryanmat, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Otrosi

  • Más estrellas que el 0% de los otros 32466 servidores de esta categoría
  • Publicado en el registro más recientemente que el 2% de los otros 32466 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 32466 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro Logicmonitor?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

Debes completar: LM_PORTAL, LM_BEARER_TOKEN, LM_ACCESS_KEY

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (1.5.1) llegó al registro hace 9 meses.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Spec Driven Development, Remote Desktop Commander, HotCodePush

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

Spec Driven Development

de formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Se ejecuta en tu computadora★ 440MITActualizado hace 14 meses
Instalar

Remote Desktop Commander

de desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Se ejecuta en la nube★ 211Actualizado ayer
Instalar

HotCodePush

de hotcodepush-team

Manage over-the-air (OTA) updates for React Native, Expo, Capacitor and Cordova apps.

Se ejecuta en la nubeActualizado hoy
Instalar

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

LogicMonitor MCP Server

Model Context Protocol (MCP) server for LogicMonitor REST API v3 integration. Enables AI assistants to interact with LogicMonitor monitoring data through 306 structured tools, 15 workflow prompts, and 26 resources. Optional integrations: IBM watsonx.ai for Granite TTM forecasting and NL summaries, Terraform IaC for any provider, and HuggingFace local Granite model fallback.

Works with any MCP-compatible client: Claude Desktop, Claude Code, Cursor, Continue, Cline, and more.

Quick Start

1. Get your LogicMonitor Bearer Token:

  • Log into your LogicMonitor portal
  • Go to Settings → Users and Roles → API Tokens
  • Create a new API-only user or add a token to an existing user
  • Copy the Bearer token

2. Configure your MCP client:

For Claude Code (CLI):

claude mcp add logicmonitor \

-e LM_PORTAL=yourcompany.logicmonitor.com \ -e LM_BEARER_TOKEN= \ -- uvx --from lm-mcp lm-mcp-server

With IBM watsonx.ai integration (optional -- adds Granite TTM forecasting and NL summaries):

claude mcp add logicmonitor \

-e LM_PORTAL=yourcompany.logicmonitor.com \ -e LM_BEARER_TOKEN= \ -e WATSONX_API_KEY= \ -e WATSONX_URL=https://us-south.ml.cloud.ibm.com \ -e WATSONX_PROJECT_ID=your-watsonx-project-id \ -- uvx --from "lm-mcp[ibm]" lm-mcp-server

With Terraform IaC (optional -- adds terraform plan/apply/generate tools):

claude mcp add logicmonitor \

-e LM_PORTAL=yourcompany.logicmonitor.com \ -e LM_BEARER_TOKEN= \ -e TF_WORKSPACE_DIR=/path/to/terraform/workspaces \ -- uvx --from lm-mcp lm-mcp-server

With HuggingFace local models (optional -- local Granite TTM + NL summaries, no cloud API needed):

claude mcp add logicmonitor \

-e LM_PORTAL=yourcompany.logicmonitor.com \ -e LM_BEARER_TOKEN= \ -- uvx --from "lm-mcp[huggingface]" lm-mcp-server

For Claude Desktop, add to your config file (see MCP Client Configuration below).

3. Verify it's working:

claude mcp list

You should see: logicmonitor: uvx --from lm-mcp lm-mcp-server - ✓ Connected

4. Test with a prompt:

"Show me all critical alerts in LogicMonitor"

What's New in v4.2.1

A fix release. LMv1 portals authenticate again, writes included: the signature follows LogicMonitor's documented recipe and covers the exact bytes sent. Tool errors reach the client with isError: true and are audited as failures, every tool is callable per its own schema, stdio starts in every configuration, and /readyz no longer calls the portal. Releases are now gated on the suite across Python 3.11 to 3.13, and the container installs from uv.lock with hash checking, digest-pinned base images, and a fixed non-root UID.

v4.2.0

What's New in v4.2.0

Multi-portal mode arrives, hardened. A single server can now serve many customer portals, selecting the active one at runtime with list_portals, use_portal, current_portal, and reload_portals — one entry in your MCP client instead of one server (and one pasted token) per portal. Credentials live in an age-encrypted vault, every portal is read-only unless its vault record says otherwise, and the mode is deliberately stdio-only: the server refuses to start it on the shared HTTP transport. The release also carries a full dependency refresh clearing 53 dependabot alerts across the lockfile.

v4.1.0

What's New in v4.1.0

Native OTLP metrics arrive. LogicMonitor's new OTLP Metrics feature (feature-flag gated, Prometheus-backed) ships in its first phase with a single UI surface (the dashboard Advanced Metrics Widget) and no Metrics Explorer yet; these four tools are the first programmatic window into that data: get_otlp_metric_names, get_otlp_metric_labels, and get_otlp_label_values for discovery, and query_otlp_metrics for full PromQL range queries returning time-series matrices. All four were validated live against a flag-enabled portal fed by a real OTel collector (Kubernetes cAdvisor and application metrics), translate the feature-disabled portal responses into a clear availability notice, and cap large matrix responses with even-stride downsampling so they stay LLM-friendly.

What's New in v4.0.0

Major. Every tool now wraps an endpoint proven to exist, validated against a live portal. Six tools that called nonexistent API paths since introduction are removed (get_cloud_cost_accounts, get_cost_summary, get_resource_cost, get_remediation_status, get_remediation_history, get_batchjob_history); the cost recommendation tools move onto the working /cost-optimization API; the Service Insight tools query real Service Insight objects (deviceType 6 devices and BizService groups) instead of the legacy v1 websites API. The Automated Diagnostics & Remediation surface arrives in full: get_diagnostic_remediation_assignments and get_diagnostic_remediation_results (structured execution records with script output, replacing audit-log scraping), execute_diagnostic, full CRUD plus import/export for diagnostic and remediation sources, and the new action chain / action rule namespace (11 tools including the set_action_rule_status toggle). update_logicmodule gains the two new source types and its apply mode actually applies now (it previously tripped its own sub-tools' confirm guards). run_report executions are pollable via get_report_execution, get_alert_details can fetch the full message body, and NextGen reports are visible to the report list tools.

Full release history, including v3.9.x and earlier, is in CHANGELOG.md. The v3.8.0 networking intelligence tools have a dedicated reference: documentation/networking-intelligence.md.

Features

306 Tools across comprehensive LogicMonitor API coverage (277 LM + 18 AAP + 10 Terraform + 1 watsonx):

Core Monitoring
  • Alert Management: Query, acknowledge, bulk acknowledge, add notes, view rules
  • Device Management: Full CRUD - list, create, update, delete devices and groups
  • Metrics & Data: Query datasources, instances, metric data, and graphs. Instance CRUD for manual datasource instances.
  • Dashboard Management: Full CRUD for dashboards, widgets, and groups
  • SDT Management: Create, list, bulk create/delete Scheduled Downtime
  • Collector Management: List collectors and collector groups
Extended Features
  • Website Monitoring: Full CRUD for synthetic checks and website groups
  • Report Management: List, view, run reports, manage schedules
  • Escalation Management: Full CRUD for escalation chains and recipient groups
  • Alert Rules: Full CRUD for alert routing rules
  • User & Role Management: View users, roles, access groups, API tokens
  • Ops Management: Audit logs, ops notes, login/change audits
  • Automated Diagnostics & Remediation: Assigned-source resolution, structured execution results with script output, diagnostic/remediation source CRUD, manual execution, action chains and rules
  • Native OTLP Metrics (preview): Metric and label discovery plus PromQL range queries against the feature-flag-gated OTLP metrics store
AI Analysis Tools

Server-side intelligence that transforms raw monitoring data into actionable insights:

  • Alert Correlation: Automatically clusters related alerts by device, datasource, and temporal proximity — replaces dozens of manual API calls with a single aggregated view
  • Alert Statistics: Aggregated alert counts by severity, top-10 devices and datasources, time-bucketed distributions for trend analysis
  • Metric Anomaly Detection: Multi-method anomaly detection (z-score, IQR, MAD) with auto-selection based on data distribution
  • Metric Baselines: Save baseline snapshots of metric behavior, then compare current performance against the baseline to detect drift
  • Scheduled Analysis: HTTP API endpoints for triggering analysis workflows (alert correlation, RCA, top talkers, health checks) from external schedulers and webhooks
ML/Statistical Analysis Tools

Pure-Python statistical methods for capacity planning, trend analysis, and operational scoring:

  • Metric Forecasting: Linear regression, Holt-Winters triple exponential smoothing, and IBM Granite TTM (via watsonx.ai, optional) with auto-selection, confidence intervals, and threshold breach prediction
  • Metric Correlation: Pearson correlation matrix across multiple metric series with strong-correlation highlighting
  • Error Budget Tracking: SLO-based error budget calculation with burn rate, projected exhaustion, and status classification
  • Change Point Detection: CUSUM algorithm for identifying regime shifts and mean-level changes
  • Alert Noise Scoring: Shannon entropy and flap detection to quantify alert noise (0-100) with tuning recommendations
  • Seasonality Detection: Autocorrelation-based periodicity detection at standard intervals with peak-hour identification
  • Availability Calculation: SLA-style uptime percentage from alert history with MTTR, incident counts, and per-device breakdown
  • Blast Radius Analysis: Topology-based downstream impact scoring for device failure scenarios
  • Change Correlation: Cross-references alert spikes with audit/change logs to identify change-induced incidents
  • Trend Classification: Categorizes metrics as stable, increasing, decreasing, cyclic, or volatile
  • Device Health Scoring: Multi-metric composite health score (0-100) using z-score analysis with configurable weights
Composite Workflow Tools

Multi-step analysis tools that combine several sub-tools into a single call. Each supports detail_level ("summary" or "full"), optional summarize=true for plain-English NL summaries via IBM Granite (requires watsonx.ai), and handles sub-tool failures gracefully with partial results.

  • Triage: Correlates active alerts, scores noise, analyzes blast radius, and cross-references recent changes
  • Health Check: Device health score, monitoring coverage, anomaly detection, active alerts, and 30-day availability
  • Capacity Plan: Per-datasource forecasting, trend classification, seasonality detection, and change point analysis
  • Portal Overview: Alert statistics, collector health, active SDTs, alert clusters, noise assessment, and down devices
  • Diagnose: Alert details, device context, correlation, blast radius, health scoring, and root cause analysis
  • Update LogicModule (Safe Partial Updates): update_logicmodule(type, id, changes, mode) exports the current full definition, deep-merges your changes, validates required fields, and returns a dry-run diff (default) or applies the merge. Prevents the full-replace blanking that wiped production Groovy scripts in two prior incidents. Supports configsource, datasource, eventsource, logsource, propertysource, topologysource.
  • Search Tools: Keyword search across all tools by name and description with category filtering
APM Trace Tools

Service discovery and RED metrics for LogicMonitor APM (Application Performance Monitoring):

  • Service Discovery: List all traced services, inspect individual service details and properties
  • Operation Listing: Discover endpoints/routes monitored within each se

Solo se muestra el principio; lee el resto en el repo

Pregunta a PopNx