<!-- omit from toc --> Vega-Lite Viewer MCP Server

A Model Context Protocol (MCP) server that enables creating interactive data visualizations using the Vega-Lite grammar. Visualizations are rendered directly inside the chat using MCP Apps — no browser window required.

• Usage
  • Prerequisites
  • Quick Start
  • CLI Reference
  • MCP Tools and Prompt
    • Tools
    • Prompt
  • Example Prompts
  • Using with MCP Inspector
  • Troubleshooting
• Contributing

Usage

Prerequisites

This server requires uv. Install it via:

# Windows
winget install --id=astral-sh.uv -e

# macOS
brew install uv

# Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

macOS note: The curl installer places uv in ~/.local/bin/ and updates your shell profile, but macOS GUI apps like Claude Desktop do not load shell startup files. Install via Homebrew to make uv visible to GUI apps.

See the uv installation guide for more options.

Quick Start

Add the following entry to your Claude Desktop configuration file (accessible via Settings... > Developer > Edit Config):

{
  "mcpServers": {
    "vegalite-viewer": {
      "command": "uv",
      "args": [
        "run",
        "--with-editable",
        "/path/to/mcp-server-vegalite-viewer",
        "mcp-server-vegalite-viewer"
      ]
    }
  }
}

Restart Claude Desktop to apply changes. The server is ready when vegalite-viewer appears in the list of connected MCP servers.

ℹ️ Note: Rendering visualizations inline in the chat requires a client that supports MCP Apps, such as Claude Desktop or Claude.ai.

CLI Reference

Flag	Description
--silent	Show only error messages
--debug	Enable detailed debug logging (also settable via VEGALITE_VIEWER_DEBUG=1)

MCP Tools and Prompt

Tools

Tool	Description
upload_data	Upload a JSON dataset and register it by name for later use in visualizations
visualize_data	Render a registered dataset as a Vega-Lite chart, displayed inline in the chat

Workflow: call upload_data first to register the dataset, then call visualize_data with a Vega-Lite specification to produce the chart. The same dataset can be visualized multiple times with different specs.

Prompt

Prompt	Description
Create a simple chart for a JSON dataset	Instructs the LLM to create a chart of a chosen type (bar, line, pie, etc.) for a provided JSON dataset

Example Prompts

Create a simple bar chart for the following JSON dataset:
[
  {"category": "Alpha",   "value": 4},
  {"category": "Bravo",   "value": 6},
  {"category": "Charlie", "value": 10},
  {"category": "Delta",   "value": 3},
  {"category": "Echo",    "value": 7},
  {"category": "Foxtrot", "value": 9}
]

Using with MCP Inspector

Create an mcp.json file:

{
  "mcpServers": {
    "vegalite-viewer": {
      "command": "uv",
      "args": [
        "run",
        "mcp-server-vegalite-viewer",
        "--debug"
      ]
    }
  }
}

Start the inspector from a terminal:

npx -y @modelcontextprotocol/inspector --config mcp.json --server vegalite-viewer

In your browser:

• Click Connect to start the server
• Go to Tools > List Tools to see the available tools
• Find server logs under Server Notifications and in %TEMP%\mcp_server_vegalite_viewer.log (Windows) or ${TMPDIR:-/tmp}/mcp_server_vegalite_viewer.log (Linux/macOS)

Troubleshooting

Visualization not rendering inline

The client must support MCP Apps. In clients without MCP Apps support the tool still works — the Vega-Lite JSON spec is returned as text, which the LLM can describe or the user can paste into Vega Editor.

Server fails to start in Claude Desktop

Check the Claude Desktop logs:

• Windows: %LOCALAPPDATA%\Claude\Logs\mcp-server-vegalite-viewer.log
• macOS: ~/Library/Logs/Claude/mcp-server-vegalite-viewer.log

Or go to Settings > Developer, select vegalite-viewer and click Open Logs Folder.

Still having issues?

Run the server with --debug and open an issue on GitHub with the relevant log output.

Contributing

See CONTRIBUTING.md for development setup, building the React app, code quality checks, and the release process.