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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Enables data observability operations with the Sifflet platform. Supports exploring assets, monitors, incidents, generating monitor-as-code YAML from descriptions, and performing impact analysis.

README.md

Sifflet MCP Server

An MCP (Model Context Protocol) server that enables data observability operations with the Sifflet platform.

Features

This project provides an MCP server enabling interactions with Sifflet API :

  • Explore assets: Search for tables, views, dashboards, and other data assets. View their schema, owners, tags, and their metadata.
  • Explore monitors: Discover existing monitors and generate their Monitor-as-Code YAML configurations.
  • Generate new monitors from a description: turn a plain-English requirement (e.g. "alert when row count drops below 1000 on the 'orders' table") into a Monitor-as-Code YAML snippet for a given list of datasets. Requires Editor role on the targeted domain.
  • Explore incidents: List all data observability incidents detected by the Sifflet platform.
  • Perform impact analysis: Start from an incident and trace the downstream assets affected.

Sample Use Cases

Here are a few scenarios where the Sifflet MCP Server can be particularly helpful:

  • Understanding Downstream Impact: You're modifying a dbt model and need to identify the owners of dependent downstream models and dashboards. The MCP server can provide these details, allowing you to proactively notify them about your upcoming changes.
  • Accessing Up-to-Date Table Metadata: You're about to update a table in your data warehouse. Before you proceed, you can query the MCP server to get its latest metadata. This includes information on how the table is currently monitored in Sifflet, whether it's involved in any ongoing incidents, the list of its frequent users, and other relevant operational details.
  • Bootstrapping New Asset Monitoring: You're creating a new table (or dbt model) and want to ensure it's well-monitored from the start. You can ask the MCP server to list the Sifflet monitors already created for similar existing assets. The server can then provide the Monitor-as-Code YAML configurations, which you can adapt and deploy.
  • Generating a Monitor from a Description: You want to export the YAML configuration of a Monitor you want to create (e.g. "alert when row count drops below 1000 on the 'orders' table"). The get_monitor_code_by_description tool returns a Monitor-as-Code YAML snippet for a given list of datasets that you can adapt and commit. Note: requires Editor role on the targeted domain (see Prerequisites).

Usage

Prerequisites

  • uv (Python package installer/environment manager)
    # uv installation script for Linux/MacOS
    curl -LsSf https://astral.sh/uv/install.sh | sh
  • A Sifflet backend running locally or remotely. You will need the following information:
  • SIFFLET_API_TOKEN: see how to generate one. A token with the Viewer

role is enough for most tools. The get_monitor_code_by_description tool additionally requires Editor role on the targeted domain. If you plan to use that tool, generate a token with Editor access on that domain.

  • SIFFLET_BACKEND_URL: Full URL to the Sifflet backend for instance: https://<tenant_name>.siffletdata.com/api/

Using with MCP Clients

Cursor

Add the following configuration in the mcp.json. Follow Cursor instructions to set it up.

{
  "mcpServers": {
    "mcp_server_sifflet": {
      "command": "uvx",
      "args": ["sifflet-mcp@latest"],
      "env": {
        "SIFFLET_API_TOKEN": "<access_token>",
        "SIFFLET_BACKEND_URL": "https://<tenant_name>.siffletdata.com/api/"
      }
    }
  }
}

Note: You may need to use the full path to the uvx executable in the command field. You can find the full path by running which uvx in your terminal.

Claude Desktop

Follow the instructions in the Claude documentation to set up claude_desktop_config.json.

Then, add the following configuration to your claude_desktop_config.json file:

{
  "mcpServers": {
    "sifflet-mcp": {
      "command": "uvx",
      "args": ["sifflet-mcp@latest"],
      "env": {
        "SIFFLET_API_TOKEN": "<access_token>",
        "SIFFLET_BACKEND_URL": "https://<tenant_name>.siffletdata.com/api/"
      }
    }
  }
}

Note: You may need to use the full path to the uvx executable in the command field. You can find the full path by running which uvx in your terminal.

Contributing

For development setup and contribution guidelines, please see CONTRIBUTING.md.

Reporting Problems

If you encounter any problems or have a bug to report, please feel free to open an issue on this GitHub repository. Alternatively, you can reach out to your Sifflet Customer Success team.

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