Connect AI Assistants to Your Uptime Monitors with MCP

What if you could ask your AI assistant: "Are any of my sites down right now?" and get an instant answer with real data from your monitoring dashboard? Today, that's exactly what UptyBots delivers.

We're releasing the UptyBots MCP Server — an integration that connects AI assistants like Claude, Cursor, and other MCP-compatible tools directly to your uptime monitors.

What is MCP?

The Model Context Protocol (MCP) is an open standard created by Anthropic that lets AI assistants interact with external tools and data sources. Think of it as a universal plug that connects your AI to the services you use every day.

Instead of switching between your monitoring dashboard and AI chat, the AI reads your monitoring data directly and responds with real numbers, real status, and real insights.

What Can You Do?

With the UptyBots MCP server, your AI assistant gets access to 15 monitoring tools:

Check status — list all monitors, filter by type (HTTP, Ping, SSL, Port, Domain, API) or status (up, down, paused)
View details — get full configuration and current state of any monitor
Create monitors — set up new HTTP, Ping, Port, SSL, Domain, or API monitors through conversation
Manage monitors — pause, resume, or delete monitors
Analyze incidents — review downtime history with timestamps and error messages
Check performance — get hourly and daily response time stats
Review notifications — see what alerts were sent and through which channels

Setup in 3 Steps

Step 1: Get an API Key

Go to Account → API Keys in your UptyBots dashboard and create a key. The key starts with upty_ and is shown only once — save it somewhere secure.

Step 2: Install the MCP Server

Clone the repository and install dependencies:

git clone https://github.com/oleprog-uptybots/mcp-server.git
cd mcp-server
npm install

Step 3: Configure Your AI Client

Add the MCP server to your client's config. Here's the Claude Desktop example:

{
  "mcpServers": {
    "uptybots": {
      "command": "node",
      "args": ["/path/to/mcp-server/index.js"],
      "env": {
        "UPTYBOTS_API_URL": "https://uptybots.com",
        "UPTYBOTS_API_KEY": "upty_your_key_here"
      }
    }
  }
}

Restart your AI client, and that's it. You can now talk to your monitors.

Real-World Use Cases

Morning check-in — "Give me a summary of all my monitors. Anything down overnight?"
Incident investigation — "What happened with my API monitor yesterday between 2pm and 4pm?"
Quick setup — "Create an HTTP monitor for staging.myapp.com with 3-minute checks"
Maintenance mode — "Pause all my staging monitors while I deploy"
Performance review — "Show me the daily response times for my main website this week"
On-call triage — "Which monitors had incidents in the last 24 hours? Show me the error messages."

Security

The MCP server runs locally on your machine. Your AI client starts it as a subprocess — no data passes through third-party servers. Authentication uses the same API keys as the REST API, with SHA-256 hashed storage and per-account data isolation.

Get Started

Ready to connect your AI assistant to your monitors? Check out the full MCP documentation for detailed setup instructions, the complete tool reference, and configuration examples for Claude Desktop, Claude Code, and Cursor.

Don't have an API key yet? Read the API docs first, or sign up free to get started.