Creating Dashboards Using Vizro MCP: Vizro is an Open-Source Python Toolkit by McKinsey

Vizro is an open-source Python toolkit by McKinsey that makes it easy to build beautiful, production-ready data visualization apps. With just a few lines of configuration (via JSON, YAML, or Python dictionaries), you can create multi-page dashboards that would normally take thousands of lines of code.

Built on top of Plotly, Dash, and Pydantic, Vizro combines the flexibility of open source with in-built best practices for design and scalability. It’s quick to learn, customizable for advanced users, and powerful enough to move from prototype to production seamlessly.

In this tutorial, we’ll use the Vizro MCP server to create a dashboard directly from Claude Desktop.

Setting up the dependencies

uv package manager

To run the Vizro server, we will need the uv package manager. Install it with the following commands:

For Mac/Linux:

Copy Code
curl -LsSf https://astral.sh/uv/install.sh | sh

For Windows:

Copy Code
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Once uv is downloaded, run the following command to get the location of uvx

For Mac/Linux:

Copy Code
which uvx

For Windows:

Copy Code
where uvx

Keep the location of uvx handy, we will need it for the config file for Claude

Claude Desktop

You can download Claude Desktop from https://claude.ai/download. Next, open the claude_desktop_config.json file located in the Claude installation directory using any text editor. If the file doesn’t exist, you can create it manually. Once opened, enter the following code:

Mac/Linux:

Copy Code
{
  "mcpServers": {
    "vizro-mcp": {
      "command": "/placeholder-path/uvx",
      "args": [
        "vizro-mcp"
      ]
    }
  }
}

Windows:

Copy Code
{
  "mcpServers": {
    "vizro-mcp": {
      "command": "placeholder-path//uvx",
      "args": [
        "vizro-mcp"
      ]
    }
  }
}

Replace the placeholder-path with the path of uvx

Running the Server

Once the file is configured, Vizro MCP Server should be visible in the list of servers.

Vizro comes with some sample datasets as well. You can try the following prompt to get started:

“create a vizro dashboard using tips dataset”

Claude will use the vizro-mcp to generate the dashboard and open it in your browser via PyCafe, showcasing interactive charts like tip vs total bill, average tips by day, tip distribution by gender, and tips by party size, along with filters for day, gender, and smoker status for seamless cross-filtering analysis.

The post Creating Dashboards Using Vizro MCP: Vizro is an Open-Source Python Toolkit by McKinsey appeared first on MarkTechPost.



from MarkTechPost https://ift.tt/myKPq7g
via IFTTT

Comments

Post a Comment

Popular posts from this blog

The entire staff of beloved game publisher Annapurna Interactive has reportedly resigned

Image
  Annapurna Interactive, the game company famous for publishing indie hits like Stray, Outer Wilds, Gorogoa, Neon White, What Remains of Edith Finch, and many more, may not be the same company anymore. Bloomberg reports that the entire staff of Annapurna Interactive, the gaming division of Megan Ellison’s Annapurna, has resigned after failing to convince Ellison to let them spin off its games division into a new company. IGN is corroborating the report. Former president Nathan Gary, Annapurna Interactive executives, and “around two dozen” staffers have resigned, Bloomberg reports. An Annapurna spokesperson told Bloomberg that existing games and projects will remain under the company. Annapurna didn’t immediately reply to a request for comment from The Verge. Last week, The Hollywood Reporter said that Gary and the coheads of Annapurna Interactive, Deborah Mars and Nathan Vella, would be leaving. THR also reported that Annapurna planned to “integrate its in-house gaming operations w...
Read more

The Art of Work: Valuing Time in the Age of AI

Image
  Artificial intelligence isn't going away. As long as there's profit to be made, advancements in AI will shape the next wave of technology. This has led to a collective despair among the creative community. While some creators are heralding AI as a valuable tool, others are leaning into AI replacements for human efforts. In reading about authors who use AI for cover/character art, I have a hot take that comes with a side of nuance: "The act of spending time on artwork doesn't qualify you to get paid for it." I probably don't mean what you think I mean. Hear me out. Recently, an author posted on Threads about using AI images for a book cover. Her reasoning was twofold: she needed a quick turnaround, and she didn't expect the profits from the upcoming promotion to cover new artwork. She mentioned that her time was an investment: "my time does have value, no?" This led to caustic responses from many users who believed that using AI for creative pur...
Read more

From Big Data to Small Data: The Next Frontier in AI Efficiency

Image
The age of Big Data has brought immense transformations across industries, particularly in the realm of artificial intelligence (AI). With vast amounts of data, AI systems have become more powerful, providing incredible insights, automating processes, and driving decision-making. However, as technology evolves, there is growing interest in shifting from Big Data to Small Data for AI efficiency. This emerging focus represents the next frontier in AI, emphasizing the value of smaller, more relevant datasets that require less computational power but yield equally impactful insights. In this blog, we’ll explore how the transition from Big Data to Small Data is revolutionizing AI development, and why mastering the concepts of data analysis through a  data science course  is essential to understanding this shift. The Era of Big Data in AI For years, the growth of AI has been fueled by Big Data—massive datasets collected from various sources like social media, sensors, and transactio...
Read more