sifflet-mcp 0.1.0

Basic MCP server for Sifflet

Sifflet MCP - AI-Powered Incident Management

A ChatGPT-like assistant for managing Sifflet incidents using Chainlit and Claude AI.

Description

This project provides an AI assistant interface for managing Sifflet data quality incidents efficiently. The assistant can perform various actions such as:

• Listing incidents
• Getting incident details
• Closing incidents
• Managing rules
• Checking asset data

Built with Chainlit, the interface provides a chat experience with AI-powered assistance backed by Claude 3.5 Sonnet.

Prerequisites

• Python 3.12+
• uv (Python package installer/environment manager)
• Sifflet backend running locally or remotely

Environment Setup

1. Clone the repository

   git clone https://github.com/siffletdata/sifflet-mcp.git
   cd sifflet-mcp
   

2. Create and activate a virtual environment with uv

   uv venv
   source .venv/bin/activate
   

3. Run the mcp server

   uv run sifflet-mcp [--sse]
   

Using with MCP Clients

If you used the installation script, the mcp server has been installed in your user directory at ~/.sifflet/sifflet-mcp/.

You will need the following information:

• <access_token>: you can find more information on how to generate it here
• <your_sifflet_backend_url>: Full URL to the Sifflet backend for instance: https://<tenant_name>.siffletdata.com/api/

Cursor

{
  "mcpServers": {
    "mcp_server_sifflet": {
      "command": "<path to repository>/.venv/bin/sifflet-mcp",
      "env": {
        "SIFFLET_API_TOKEN": "<access_token>",
        "SIFFLET_URL": "<your_sifflet_backend_url>"
      }
    }
  }
}

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": "<path to repository>/.venv/bin/sifflet-mcp",
      "env": {
        "SIFFLET_API_TOKEN": "<access_token>",
        "SIFFLET_URL": "<your_sifflet_backend_url>"
      }
    }
  }
}

Development

uv run pre-commit install

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