Monte Carlo
About
Monte Carlo provides data and AI observability for monitoring data reliability. Its connector gives assistants observability context for investigating data incidents, understanding quality signals, and supporting trusted analytics workflows.
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- Monte Carlo
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Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Monte CarloCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
{
"mcpServers": {
"monte-carlo": {
"type": "http",
"url": "https://integrations.getmontecarlo.com/mcp"
}
}
}
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"monte carlo": {
"monte-carlo": {
"type": "http",
"url": "https://integrations.getmontecarlo.com/mcp"
}
}
}
}McpServers
{
"monte-carlo": {
"type": "http",
"url": "https://integrations.getmontecarlo.com/mcp"
}
}Monte Carlo provides data and AI observability for monitoring data reliability. Its connector gives assistants observability context for investigating data incidents, understanding quality signals, and supporting trusted analytics workflows.
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