"Apache Spark" matching MCP servers:

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

MCP gateway to World Labs Marble + Spark 2.0 for generating navigable 3D worlds from text, images, panoramas, multi-view sets, or video, and grounding a voice agent in scene coordinates.

Generates Apache ECharts diagrams and charts with AI dynamically, supporting all ECharts features and exporting to png, svg, and option formats.

Enables deterministic reconstruction of complex tables from OCR bounding boxes, including multi-column layouts, merged headers, grid hierarchies, formula auditing, and PII redaction through MCP.

Enables AI agents to fuse 2D/3D visual bounding boxes, user head-pose gaze vectors, and acoustic beamforming azimuth angles into cross-modal focal salience scores. It also resolves deictic spatial references in real time, running as a zero-dependency Python MCP server over JSON-RPC stdio.

Enables autonomous shortform video editing by converting 16:9 footage to 9:16 with dynamic speaker tracking, smart reframing bounding boxes, audio silence pacing, and precise cut-list generation through MCP-compatible clients.

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

Enables autonomous agents to orchestrate HubX mobile AI tools for plant and nutrition vision diagnostics, voice transcription and summarization, photo-realistic portrait and art generation, and interior/exterior spatial design through structured JSON outputs.

Enables audio silence detection and jumpcut cadence/pacing analysis for shortform video editing, producing precise cut-lists and telemetry through the Model Context Protocol.

Enables edge robotics to slice LiDAR/depth point clouds into 2.5D occupancy grids, computing spatial obstacles for real-time telemetry and actuator safety supervision.

Enables generating images, videos, characters, and scenes through Google Flow. Supports SSE and Vercel deployment for integration with Gemini Spark and other IDEs.

Enables AI agents to compare visual specifications and calculate physical dimensions and degrees of freedom from multimodal inputs.

Enables high-resolution image canvas processing by slicing images into spatial grid tiles and blending seams for seamless generative upscaling, compatible with Magnific AI / Krea AI workflows.

Provides multimodal OCR table grid and merged-cell reconstruction into Markdown, and integrates with MCP-compliant clients like Claude Desktop and Cursor.

Enables MCP clients to score the retention quality of the first three seconds of shortform video hooks using audio/video telemetry and transcript input, returning deterministic JSON results for viral hook optimization.