Visuals MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Visuals MCP Server Show me a table of user data with sorting and filtering"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Visuals Server
An MCP (Model Context Protocol) server that provides interactive visualizations for AI agents. Display data in rich, interactive formats including tables with TanStack Table, charts with Recharts, image previews with metadata, master-detail views for browsing collections, tree views for hierarchical data, and customizable lists with drag-and-drop reordering.
Quick Install
°°°
Features
Table Visualization
Interactive Table Display: Full-featured data table with TanStack Table v8
Sorting: Click column headers to sort ascending/descending
Filtering: Per-column text filters with apply button
Pagination: Customizable page sizes (5, 10, 20, 50, 100 rows)
Column Visibility: Toggle which columns are displayed
Row Selection: Select individual rows or all rows
Export: Copy as CSV/TSV or export to PDF
Agent Integration: Table state (selections, filters, sorting) automatically sent back to the LLM via
updateModelContextTheme Integration: Respects VS Code theme colors and fonts
Responsive: Works on different screen sizes
Generic Data Support: Accepts any column structure and data types
Chart Visualization
Interactive Charts: Render line, bar, area, pie, scatter, and composed charts
Multiple Charts Per View: Show several charts together in vertical, horizontal, or grid layouts
Flexible Series Configuration: Configure named series, custom colors, stacked bars/areas, and mixed composed charts
Rich Chart Features: Optional legends, tooltips, grid lines, and dual Y-axes
Export Options: Copy chart payloads as JSON or CSV directly from the UI
Agent Awareness: Active chart selection and hover state can be reported back to the host app
Theme Integration: Respects VS Code theme colors and fonts
Responsive: Adapts to narrow panels and wider layouts
Image Preview
Rich Image Cards: Display images with title, caption, and metadata
Metadata Display: Show filename, dimensions, and file size
Flexible Sources: Support URLs and data URIs
Local File Support: Automatically converts local file paths to data URIs
Theme Integration: Respects VS Code theme colors and fonts
Master-Detail View
Flexible Layout: Display a list of items with detailed content panel
Multiple Content Types: Detail panel supports tables, images, or custom text/HTML
Reusable Components: Leverages existing table and image visualizations
Configurable Layout: Choose horizontal (side-by-side) or vertical (stacked) orientation
State Management: Selection state automatically sent back to LLM
Rich Master List: Display items with icons, labels, and descriptions
Theme Integration: Consistent theming across all components
Tree View
Hierarchical Data Display: Interactive tree structure for nested data
Expand/Collapse: Click to expand or collapse nodes
Node Selection: Select individual nodes to highlight them
Metadata Support: Display optional metadata for each node
Icons: Add custom icons/emojis to nodes
Bulk Operations: Expand all or collapse all nodes at once
Export Options: Copy tree to clipboard, export as HTML, or save as image (PNG)
Agent Integration: Tree state (expanded nodes, selection) sent back to the LLM
Theme Integration: Respects VS Code theme colors and fonts
Use Cases: File systems, org charts, nested categories, JSON/XML structures
List Visualization
Interactive Lists: Display any type of list with rich formatting
Drag-and-Drop Reordering: Easily reorder items by dragging
Checkboxes: Optional checkboxes for task lists and selections
Image Thumbnails: Show images alongside list items
Compact Mode: Toggle between comfortable and compact layouts
Export Options: Copy as plain text, CSV, or JSON
Individual Item Copy: Quick copy button for each item
Subtext Support: Secondary text/description for each item
Metadata: Attach custom metadata to items
Theme Integration: Respects VS Code theme colors and fonts
Related MCP server: Interactive Feedback MCP
Screenshots

Interactive table with sorting, filtering, pagination, and row selection

Interactive chart dashboard with multiple chart types and grid layout

Master-detail view for browsing collections with tables, images, or custom content

Interactive list with drag-and-drop reordering, checkboxes, and image thumbnails

Interactive tree view with expand/collapse, node selection, and export options
Installation
VSCode Extension (Easiest)
Install directly from the VS Code Marketplace:
Open VS Code
Go to Extensions (Ctrl+Shift+X / Cmd+Shift+X)
Search for "Visuals MCP"
Click Install
The extension will automatically register the MCP server with VS Code and GitHub Copilot Chat.
npmjs (Recommended for other MCP Clients)
In VSCode github Copilot Chat
click on the tools icon (Configure tools...)
click on "Add MCP Server"
click on "Install from npm"
enter
@harrybin/visuals-mcppress enter / click "Install"
Using command line:
npm install -g @harrybin/visuals-mcp
visuals-mcpGitHub Packages
Authenticate npm with GitHub Packages:
npm config set @harrybin:registry https://npm.pkg.github.com
npm config set //npm.pkg.github.com/:_authToken=YOUR_GITHUB_TOKENInstall and run:
npm install -g @harrybin/visuals-mcp
visuals-mcpLocal Development
# Install dependencies
npm install
# Build all UI bundles and the server
npm run build
# Optional: rebuild only the chart UI bundle
npm run build:charts
# Run the server
npm run serveChart Tool
Use display_chart to render one or more interactive charts in the MCP client.
Supported chart types:
linebarareapiescattercomposed
Repository Metrics Dashboard Example
Generate fresh metrics first:
npm run metrics:repo:writeThis writes a snapshot to doc/repo-metrics.json.
Then render a dashboard that uses all chart types (line, bar, area, pie, scatter, composed):
For release-quality docs, always regenerate doc/repo-metrics.json right before updating README examples.
1. Configure MCP Server
For VS Code: This workspace includes MCP configuration in .vscode/settings.json.
To add globally, update your VS Code settings:
{
"github.copilot.chat.mcpServers": {
"visuals-mcp": {
"type": "stdio",
"command": "node",
"args": [
"dist/server.js"
]
}
}
}For Claude Desktop: See claude_desktop_config.json for example configuration.
License
MIT
Contributing
Contributions welcome! Please open an issue or PR.
Resources
Available Tools
7 toolsdisplay_chartDisplay ChartA
Display interactive charts with support for multiple chart types: line, bar, area, pie, scatter, and composed charts. Use this to visualize data trends, comparisons, distributions, and relationships. Supports multiple charts in a single view with customizable layouts (vertical, horizontal, grid). Features include legends, tooltips, grid lines, dual Y-axes, and data export (JSON, CSV).
Inputs: charts (required), title, layout.
display_imageDisplay ImageA
Display/show any image to the user with an interactive preview card. Use this tool to show screenshots, diagrams, charts, photographs, or any visual content. Provides optional metadata including title, caption, dimensions, and file information. Always use this tool whenever you need to present visual content. This also applies to listings and any other imageoperations like get, download etc..these formats are explicitly handled: PNG, JPG, JPEG, GIF, SVG, WebP, BMP. The UI itself can display any image if the src is a valid URL or data URI, but local file paths are only auto-converted for those extensions
Inputs: src (required), title, alt, caption, +4 more.
display_listDisplay ListA
Display an interactive, customizable list with optional checkboxes, drag-and-drop reordering, image thumbnails, and copy/export functionality. Perfect for displaying any type of list: tasks, items, options, files, or any sequential data. Features include compact/comfortable views, individual item copy, and bulk export (CSV, JSON, text).
Inputs: items (required), title, allowReorder, allowCheckboxes, +2 more.
display_master_detailDisplay Master DetailA
Display a master-detail view with a list of items on the left/top and details on the right/bottom. The detail panel can show tables, images, lists, or custom text/HTML content. Perfect for browsing collections, comparing items, or navigating hierarchical data.
Inputs: masterItems (required), detailContents (required), title, defaultSelectedId, +2 more.
display_tableDisplay TableB
Display an interactive table with sorting, filtering, pagination, column visibility, and row selection. Accepts column definitions and row data. Returns a visual table component that users can interact with.
Inputs: columns (required), rows (required), title, allowRowSelection, +2 more.
display_treeDisplay TreeA
Display an interactive tree view for hierarchical data structures. Use this tool to visualize file systems, organizational charts, nested categories, JSON/XML structures, or any hierarchical relationships. Supports node expansion/collapse, metadata display, and export functionality.
Inputs: nodes (required), title, expandAll, showMetadata.
query_table_dataQuery Table DataB
Query table data with server-side sorting and filtering. UI-only tool for performance with large datasets.
Inputs: sortBy, filters, page, pageSize.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 7 tools
Each tool has a clearly distinct purpose (chart, image, list, master-detail, table, tree) with no overlap. The query_table_data tool is also distinct as a data manipulation utility. An agent can easily distinguish them.
Most tools follow a consistent 'display_<type>' pattern, making them predictable. The single outlier, query_table_data, uses a different verb and structure but is still understandable and serves a different function.
With 7 tools, the server covers a variety of visual display needs without being overwhelming. Each tool earns its place, and the count is appropriate for a focused visual display server.
The tool set covers common visualizations like charts, images, tables, lists, trees, and master-detail views. It lacks some specialized types (e.g., maps, timelines) but provides a solid foundation for most use cases.
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