"Apache Spark" matching MCP servers:

Connects LLM clients to Apache Superset for querying charts, dashboards, datasets, databases, and executing SQL.

A Model Context Protocol server that renders Apache ECharts options to SVG, enabling AI agents to generate deterministic charts server-side without a browser.

Enables AI to create and manage Apache Superset dashboards, including adding charts and native filters from datasets.

Local stdio MCP server for reviewing Apache Superset dashboards, retrieving chart data, executing SQL through SQL Lab, and creating or updating saved queries.

MCP server for Preset (managed Apache Superset). Manage dashboards, charts, and datasets from Claude Code and other LLM agents.

An MCP server that provides AI assistants with full access to Apache Superset instances, enabling interaction with dashboards, charts, datasets, databases, and SQL execution capabilities.

A Model Context Protocol (MCP) server for managing Apache Superset datasets, metrics, and SQL queries.

Enables AI assistants to perform data analysis on local datasets through natural language, orchestrating Python, R, SQL, Spark, Jupyter, Power BI, and Tableau engines for statistics, machine learning, dashboard generation, and batch processing.

Enables AI agents to generate safe, runnable HTML chart pages from structured JSON data using Apache ECharts. It provides tools for chart type recommendation, page generation, validation, and patching with controlled, deterministic output.

A comprehensive MCP server for Apache Superset. Gives AI assistants full control over your Superset instance — dashboards, charts, datasets, SQL Lab, users, roles, RLS, and more — through 137 tools.

Enables transforming raw enterprise documents, meeting transcripts, and KPI metrics into structured executive slide decks with layout templates, card callouts, speaker notes, and timing budgets through MCP-compatible workflows.

An MCP server for generating offline charts using Apache ECharts SVG SSR and rsvg-convert, optimized for Kylin ARM64 with 64KB page size.

Enables AI agents to manage Apache Superset BI metadata (charts, dashboards, datasets, and queries) via MCP, with a read-only default and optional governed write access.

Enables AI agents to perform deterministic search synthesis and compile Sparkpage layouts into comparison matrices and ready-to-render HTML interfaces through a zero-dependency Python MCP server. Plugs into Claude Desktop, Cursor, and other MCP clients for structured, low-latency output with execution telemetry.

Enables autonomous agents to synthesize heterogeneous search results into interactive comparison layouts (Genspark Sparkpages) via MCP, with deterministic JSON schema validation and zero-dependency execution.

Connects MCP clients like Claude, Codex, and Cursor to a running Autodesk Revit session for typed BIM queries, verified model edits, family authoring, exports, and Power BI workflows. It is open-source, Apache-2.0, and designed for reliable, verified outcomes.

Enables users to calibrate multimodal chart coordinates and recover tabular datasets from visual bar, line, and scatter charts as structured numbers.