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Logicmonitor

作者:ryanmat版本 1.5.1i★ –i在你的电脑上运行
注册名称io.github.ryanmat/logicmonitor

安装

概览

作者提供的说明(英文原文)

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

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他
  • 你需要填写:LM_PORTAL, LM_BEARER_TOKEN, LM_ACCESS_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: LM_PORTAL, LM_BEARER_TOKEN, LM_ENABLE_WRITE_OPERATIONS, LM_ACCESS_ID, LM_ACCESS_KEY, LM_ENABLED_TOOLS, LM_DISABLED_TOOLS, LM_LOG_LEVEL

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 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"
      }
    }
  }
}

在终端中运行这条命令

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

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.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"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "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"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • LM_PORTAL 必填 env
    LogicMonitor portal hostname (e.g., company.logicmonitor.com)
  • LM_BEARER_TOKEN 机密 必填 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 机密 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)

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 ryanmat 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32417 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32417 个服务器的 2% 更新
  • 基础检查结果等于或优于此分类中其他 32417 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Logicmonitor 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:LM_PORTAL, LM_BEARER_TOKEN, LM_ACCESS_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.5.1)于9个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, FOGA node

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

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

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

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

在云端运行★ 211昨天更新
安装

FOGA node

作者:garyyang-finchip

A Finch OG Agent cell as an MCP server: read the world, dry-run and take ERC-8414 tenders by policy.

电脑或云端今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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

只显示了开头部分;其余内容请在仓库中阅读

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