"Checking Supabase migrations in GitHub Actions" matching MCP servers:

Enables AI assistants to query GitHub trending projects, analyze language and technology trends, and generate visual trend reports.

Embeds live, interactive Tableau dashboards in ChatGPT, pushing mark selections to the model so questions about specific data points are answered with live queried numbers.

Renders word-sized charts — sparklines, bars, bullets and 100+ more types — to self-contained SVG with generated alt text, small enough to sit inline in a model's reply or a table cell. Three tools: find the right chart for a question, get its wiring, and render it.

MCP server that lets agents create, display, and export rich UI widgets (cards, dashboards, charts, forms) inline in conversations, with interactive iframe support in MCP Apps hosts and PNG image fallback for other clients.

MCP server for creating interactive Vega-Lite data visualizations that render inline in chat via MCP Apps.

MCP server that provides a live, terminal-native layered dependency map for AI coding assistants, with tools to track and visualize development progress in real time.

An MCP server that generates diagrams from Mermaid code in multiple formats (PNG, PDF, SVG).

An MCP server that lets Claude or ChatGPT read, create, and edit mind maps stored in a GitHub repository, with support for local and HTTP transport.

Turns a CSV — or a public dataset named in plain English — into an animated chart video. Every numeric claim in the generated narration is recomputed from the source rows before export, and a claim that does not reconcile blocks the export rather than shipping.

Enables AI agents to render interactive user interfaces such as forms, dashboards, charts, tables, and wizards directly in MCP-compatible clients. Supports structured data collection and richer interactions beyond text responses.

TableCharts MCP Server gives any LLM assistant the ability to instantly convert tabular data into beautiful, hosted, interactive dashboards. Simply provide JSON rows, raw CSV text, or a public URL (Notion page, Google Sheet, or Salesforce report), and get back a shareable dashboard URL plus an embeddable iframe code — all in one tool call. Supports 6 chart types: bar, line, area, pie, scatter, a

An MCP server that enables LLMs to create and open diagrams in draw.io using XML, Mermaid, or CSV formats, by building a URL with compressed content and opening it in the browser.

diagramzu-mcp lets an AI client (Claude, Cursor, ChatGPT, etc.) author Mermaid diagrams in a shared workspace that a team can read, comment on, embed, and present at a clean URL — rather than just generating a one-off diagram. Hosted endpoint https://mcp.diagramzu.ai/mcp or local npx -y @diagramzu/mcp. Also listed in the official MCP registry as ai.diagramzu/mcp.

A local MCP server that renders a database schema as an interactive, dbdiagram.io-style ER diagram in your browser.

Enables AI agents to render interactive Highcharts visualizations directly within VS Code chat conversations. It supports over 17 chart types with GitHub Primer styling and advanced features like drilldown and WebGL rendering.

Creates Tableau workbooks from a declarative JSON spec, validates them by opening in the installed Tableau Public application, and publishes to Tableau Public through the desktop UI.

Exposes read-only account-health tools for scores, trends, claims checks, risks, pipeline, and next actions, with audience-scoped output for internal or customer views.

Enables AI agents to create and edit Figma Slides in real-time, with built-in renderers for D3 charts, Rough.js sketches, and Satori layouts.

Enables AI assistants and teams to collaborate in a shared workspace by building and querying tables, writing documents, uploading files, and publishing live dashboards through any MCP-compatible client.

Enables LLMs to create and open diagrams in the draw.io editor, supporting inline chat previews via MCP Apps, direct editor opening with XML/CSV/Mermaid format support, and diagram export to PNG/SVG/PDF or browser URLs through multiple integration approaches.