sifflet-mcp 0.1.3

MCP server for interaction with Sifflet data observability platform

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.
• 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.

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: you can find more information on how to generate it here
  • 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": "uv run --with sifflet-mcp --no-project sifflet-mcp",
      "env": {
        "SIFFLET_API_TOKEN": "<access_token>",
        "SIFFLET_BACKEND_URL": "https://<tenant_name>.siffletdata.com/api/"
      }
    }
  }
}

Claude

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"],
      "env": {
        "SIFFLET_API_TOKEN": "<access_token>",
        "SIFFLET_BACKEND_URL": "https://<tenant_name>.siffletdata.com/api/"
      }
    }
  }
}

Development

Environment Setup

# clone the repository
git clone https://github.com/siffletdata/sifflet-mcp.git
cd sifflet-mcp
# create a virtual environment
uv venv
# install pre-commit
uv run pre-commit install
# run the server
uv run sifflet-mcp [--sse]

# Cursor setup: mcp.json or equivalent 
# You may need to put the full path to the uv executable in the command field. You can get this by running `which uv` on MacOS/Linux or `where uv` on Windows.
uv --directory <PATH_TO_PARENT_FOLDER>/sifflet-mcp run src/sifflet_mcp/server.py

To add new features or tools:

1. Add new tool functions in server.py using the @mcp.tool decorator
2. The server will automatically discover and use these tools