A Model Context Protocol (MCP) server that provides seamless integration between AI assistants and Prometheus, enabling natural language interactions with your monitoring infrastructure. This server allows for effortless querying, discovery, and analysis of metrics through Visual Studio Code, Cursor, Windsurf, Claude Desktop, and other MCP clients.

• Fast and lightweight. Direct API integration with Prometheus, no complex parsing needed.
• LLM-friendly. Structured JSON responses optimized for AI assistant consumption.
• Configurable capabilities. Enable/disable tool categories based on your security and operational requirements.
• Dual transport support. Works with both stdio and HTTP transports for maximum compatibility.

• Node.js 20.19.0 or newer
• Access to a Prometheus server
• VS Code, Cursor, Windsurf, Claude Desktop or any other MCP client

First, install the Prometheus MCP server with your client. A typical configuration looks like this:

{
  "mcpServers": {
    "prometheus": {
      "command": "npx",
      "args": ["prometheus-mcp@latest", "stdio"],
      "env": {
        "PROMETHEUS_URL": "http://localhost:9090"
      }
    }
  }
}

# For VS Code
code --add-mcp '{"name":"prometheus","command":"npx","args":["prometheus-mcp@latest","stdio"],"env":{"PROMETHEUS_URL":"http://localhost:9090"}}'

# For VS Code Insiders
code-insiders --add-mcp '{"name":"prometheus","command":"npx","args":["prometheus-mcp@latest","stdio"],"env":{"PROMETHEUS_URL":"http://localhost:9090"}}'

{
  "mcpServers": {
    "prometheus": {
      "command": "npx",
      "args": ["prometheus-mcp@latest", "stdio"],
      "env": {
        "PROMETHEUS_URL": "http://localhost:9090"
      }
    }
  }
}

{
  "mcpServers": {
    "prometheus": {
      "command": "npx",
      "args": ["prometheus-mcp@latest", "stdio"],
      "env": {
        "PROMETHEUS_URL": "http://localhost:9090"
      }
    }
  }
}

{
  "mcpServers": {
    "prometheus": {
      "command": "npx",
      "args": ["prometheus-mcp@latest", "stdio"],
      "env": {
        "PROMETHEUS_URL": "http://localhost:9090"
      }
    }
  }
}

Prometheus MCP server supports the following arguments. They can be provided in the JSON configuration above, as part of the "args" list:

> npx prometheus-mcp@latest --help

Commands:
  stdio  Start Prometheus MCP server using stdio transport
  http   Start Prometheus MCP server using HTTP transport

Options:
  --help     Show help                          [boolean]
  --version  Show version number                [boolean]

You can also configure the server using environment variables:

• PROMETHEUS_URL - Prometheus server URL
• ENABLE_DISCOVERY_TOOLS - Set to "false" to disable discovery tools (default: true)
• ENABLE_INFO_TOOLS - Set to "false" to disable info tools (default: true)
• ENABLE_QUERY_TOOLS - Set to "false" to disable query tools (default: true)

When running in server environments or when you need HTTP transport, run the MCP server with the http command:

npx prometheus-mcp@latest http --port 3000

And then in your MCP client config, set the url to the HTTP endpoint:

{
  "mcpServers": {
    "prometheus": {
      "command": "npx",
      "args": ["mcp-remote", "http://localhost:3000/mcp"]
    }
  }
}

Run the Prometheus MCP server using Docker:

{
  "mcpServers": {
    "prometheus": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--init",
        "--pull=always",
        "-e",
        "PROMETHEUS_URL=http://host.docker.internal:9090",
        "ghcr.io/idanfishman/prometheus-mcp",
        "stdio"
      ]
    }
  }
}

The Prometheus MCP server provides 10 tools organized into three configurable categories:

Here are some example interactions you can have with your AI assistant:

• "Show me all available metrics in Prometheus"
• "What's the current CPU usage across all instances?"
• "Get the memory usage for the last hour"

• "List all scrape targets and their status"
• "What labels are available for the http_requests_total metric?"
• "Show me all metrics related to 'cpu'"

• "Compare CPU usage between production and staging environments"
• "Show me the top 10 services by memory consumption"
• "What's the error rate trend for the API service over the last 24 hours?"

• Network Access: The server requires network access to your Prometheus instance
• Resource Usage: Range queries can be resource-intensive; monitor your Prometheus server load

• Verify your Prometheus server is accessible at the configured URL
• Check firewall settings and network connectivity
• Ensure Prometheus API is enabled (default on port 9090)

• Verify the MCP server has network access to Prometheus
• Check if authentication is required for your Prometheus setup

• If certain tools are missing, check if they've been disabled via configuration

This project is licensed under the MIT License - see the LICENSE file for details.

• GitHub Issues: Report bugs or request features
• Documentation: Model Context Protocol Documentation
• Prometheus: Prometheus Documentation

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