Uptimebolt Mcp Server

io.github.clm-cloud-solutionsPublished by GitHub account clm-cloud-solutionsv1.0.7Updated Oct 24, 2026

AI-powered infrastructure monitoring — health, incidents, predictions, RCA, deploy safety

Overview

AI-generated overview

UptimeBolt's MCP server lets an AI assistant query infrastructure monitoring data — service health, incidents, predictions, root cause analysis and deploy…

What you can do
  • Check service and monitor health, status, response times and uptime
  • Review active and resolved incidents with optional AI root cause analysis
  • Get AI predictions of upcoming issues with confidence and predicted impact
  • List recent deployments with automatic GitHub/GitLab incident correlation
  • Run multi-model root cause analysis and get a deploy safety verdict
  • Produce an executive summary of infrastructure health for reports or standups
When to use it
Useful for DevOps and SRE teams already on UptimeBolt who want to ask about infrastructure health in natural language, investigate incidents and deploy correlation, or gate CI/CD pipelines on a deploy safety check.
Requirements
Runs locally over stdio via the npm package (Node.js), or as an HTTP/Docker service. Needs an UptimeBolt account and API key: UPTIMEBOLT_API_KEY for stdio, or an x-api-key header in HTTP mode. UPTIMEBOLT_API_URL sets the API base URL. Network access to the UptimeBolt API.
Before you install
Requires an UptimeBolt API key, which grants access to your monitoring data; keep it out of shared configs and logs. Monitoring data, including deploy and incident details, is sent to the UptimeBolt API and its AI analysis models. The server is read-oriented, but the deploy safety result may be used to gate real deployments.

Installation

In SourceWeft

  1. Open Uptimebolt Mcp Server in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

UptimeBolt MCP Server

AI-powered infrastructure monitoring tools for Claude, Claude Code, Cursor, and any MCP-compatible client.

UptimeBolt is an AI-first monitoring platform that groups monitors into logical business services, predicts cascade failures before they happen, and automatically identifies which deploy caused each incident — including the commit, files, and lines of code responsible.

Built by CLM Cloud Solutions in Madrid, Spain.

Why UptimeBolt MCP Server?

Ask your infrastructure questions in natural language. Instead of navigating dashboards, let your AI assistant query real-time monitoring data directly:

  • "Is it safe to deploy right now?" — get a data-driven answer based on health scores, active incidents, and predictions
  • "What caused the last incident?" — AI-powered root cause analysis with deploy correlation
  • "Give me an executive summary of the last 24 hours" — ready for your standup or status report
  • "Show me monitors that are degraded" — instant filtered view across your infrastructure

Features

  • 10 monitoring tools — service status, incidents, predictions, RCA, deploy safety, and more
  • Dual transport — stdio (local) + HTTP (remote/CI-CD)
  • API key authentication — secure per-request access to your UptimeBolt data
  • Works everywhere — Claude Desktop, Claude Code, Cursor, Cline, and any MCP client
  • CI/CD ready — deploy safety checks directly in your pipeline

Quick Start

Install globally (recommended)

bash
npm install -g @uptimebolt/mcp-server

Claude Desktop (stdio)

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

json
{  "mcpServers": {    "uptimebolt": {      "command": "uptimebolt-mcp",      "env": {        "UPTIMEBOLT_API_KEY": "your-api-key",        "UPTIMEBOLT_API_URL": "https://api.uptimebolt.io"      }    }  }}

Or without global install, using npx:

json
{  "mcpServers": {    "uptimebolt": {      "command": "npx",      "args": ["-y", "--package=@uptimebolt/mcp-server", "uptimebolt-mcp"],      "env": {        "UPTIMEBOLT_API_KEY": "your-api-key",        "UPTIMEBOLT_API_URL": "https://api.uptimebolt.io"      }    }  }}

Claude Code / Cursor

Add to your project's .mcp.json:

json
{  "mcpServers": {    "uptimebolt": {      "command": "uptimebolt-mcp",      "env": {        "UPTIMEBOLT_API_KEY": "your-api-key",        "UPTIMEBOLT_API_URL": "https://api.uptimebolt.io"      }    }  }}

Docker (HTTP)

bash
docker run -p 3100:3100 \  -e UPTIMEBOLT_API_URL=https://api.uptimebolt.io \  ghcr.io/clm-cloud-solutions/uptimebolt-mcp-server:latest

Then connect via mcp-remote:

json
{  "mcpServers": {    "uptimebolt": {      "command": "npx",      "args": ["-y", "mcp-remote", "http://localhost:3100/mcp", "--header", "x-api-key:your-api-key"]    }  }}

npm (programmatic)

bash
npm install @uptimebolt/mcp-server
typescript
import { TOOLS, HANDLERS } from "@uptimebolt/mcp-server";
// TOOLS — MCP tool definitions (10 tools)// HANDLERS — tool handler functions: (args, context?) => Promise<result>

Available Tools

ToolDescription
get_service_statusHealth status of business services with health score (0-100), monitor breakdown, and active incidents
get_monitorsList all monitors with operational status, response time, and uptime percentage
get_monitor_healthDetailed health for a specific monitor including response time trends and active predictions
get_monitor_metricsResponse time stats (avg, p95, p99), uptime percentage, and error breakdown
get_incidentsActive and resolved incidents with optional AI root cause analysis details
get_predictionsAI predictions for upcoming issues with confidence levels and predicted impact
get_deploymentsRecent deployments with automatic incident correlation (GitHub/GitLab)
run_root_cause_analysisAI-powered RCA using multi-model analysis (Claude, GPT) with deploy correlation
is_safe_to_deployCI/CD deploy safety check based on health scores, predictions, and active incidents
get_executive_summaryInfrastructure health summary for standups, weekly reports, or status updates

Authentication

Get your API key at app.uptimebolt.io/settings/api-keys.

  • stdio mode: Set UPTIMEBOLT_API_KEY environment variable
  • HTTP mode: Pass x-api-key header with each request (no startup key required)

CI/CD Integration

Use is_safe_to_deploy as a gate in your deployment pipeline:

bash
curl -X POST http://localhost:3100/mcp \  -H "Content-Type: application/json" \  -H "Accept: application/json, text/event-stream" \  -H "x-api-key: your-api-key" \  -d '{    "jsonrpc": "2.0",    "id": 1,    "method": "tools/call",    "params": {      "name": "is_safe_to_deploy",      "arguments": { "service_name": "my-service" }    }  }'

The response includes a risk level (low, medium, high), active issues, and a recommendation (proceed, proceed_with_caution, wait_and_monitor).

Configuration

VariableDescriptionDefault
UPTIMEBOLT_API_KEYYour UptimeBolt API key(required for stdio)
UPTIMEBOLT_API_URLUptimeBolt API base URLhttp://localhost:3200
MCP_HTTP_PORTHTTP server port3100
NODE_ENVEnvironment (production disables console logs)development
LOG_LEVELLog level (error, warn, info, debug)debug (dev) / info (prod)

Development

bash
git clone https://github.com/clm-cloud-solutions/uptimebolt-mcp-server.gitcd uptimebolt-mcp-servercp .env.example .env          # configure your environmentnpm installnpm run dev          # stdio modenpm run dev:http     # HTTP modenpm run build        # compile TypeScriptnpm run typecheck    # type check without emitting

About UptimeBolt

UptimeBolt is an AI-first SaaS monitoring platform for DevOps teams and SREs. Key capabilities:

  • Cascade failure prediction — dependency graph with what-if analysis, downtime cost estimation, and proactive mitigations
  • Deploy correlation + RCA 2.0 — automatically correlates GitHub/GitLab deploys with incidents, identifies the responsible commit and files
  • AI Copilot — conversational assistant with real-time infrastructure context
  • 8 monitor types — HTTP, TCP, DNS, Database, Email, Synthetic, Push, Ping

About CLM Cloud Solutions

CLM Cloud Solutions S.L. is a technology company based in Madrid, Spain, building SaaS products for engineering teams to operate with confidence, speed, and security.

License

MIT

Source: README.md at commit 736a07b

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.0.7LatestSep 16, 2026

Score

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