KyuRish/mcp-dashboards

Overview

KyuRish/mcp-dashboards is a TypeScript MCP server that generates interactive dashboards from data within any MCP-compatible AI client. It processes data inputs and renders them as visual charts or tables directly in the client interface.

Best for

Best for
Developers who want to embed data dashboards directly inside MCP-compatible AI assistants

Use cases

• Embed live data visualizations in AI chat sessions
• Build quick dashboards from CSV or API data without leaving the client
• Monitor metrics or logs through interactive charts inside an MCP host

How to use

Install

npx mcp-dashboards

Tools exposed

• render_pie_chart
• render_bar_chart
• render_line_chart
• render_scatter_chart
• render_candlestick_chart
• render_radar_chart
• render_treemap_chart
• render_sankey_chart
• render_wordcloud_chart
• render_boxplot_chart
• render_live_chart
• poll_http
• render_bullet_chart
• render_lollipop_chart
• render_dumbbell_chart
• render_variance_chart
• render_funnel_chart
• render_slope_chart
• render_waffle_chart
• render_sparkline_chart

Tested with

Claude Desktop, Claude Code, VS Code, ChatGPT

Example client config

{\n  "mcpServers": {\n    "dashboard": {\n      "command": "npx",\n      "args": ["-y", "mcp-dashboards", "--stdio"]\n    }\n  }\n}

Notes

KyuRish/mcp-dashboards is a TypeScript MCP server that generates interactive dashboards from data within any MCP-compatible AI client. It processes data inputs and renders them as visual charts or tables directly in the client interface.

29 stars on GitHub. Last updated 2026-05-11.

Use cases

• Embed live data visualizations in AI chat sessions
• Build quick dashboards from CSV or API data without leaving the client
• Monitor metrics or logs through interactive charts inside an MCP host

Pros

• Works with any MCP-compatible AI client for broad integration
• Lightweight TypeScript implementation with low overhead
• Enables real-time data exploration within conversational workflows

Cons

• Limited to MCP ecosystem, not standalone or web-based
• Small community (29 stars) with minimal documentation or examples
• Dependent on client support for interactive rendering features

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.