"Apache ECharts" 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.

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

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.

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

Enables inspection and management of Apache Airflow DAGs, runs, and logs across multiple instances. It provides tools for monitoring workflows and performing gated write operations like triggering DAGs or clearing task instances.

Enables lookups across Apache Iceberg Javadocs, local source evidence, and Iceberg REST Catalog operations through MCP tools and prompts.

An MCP server for rendering common ECharts visualizations from structured tool arguments, exposing per-chart opener tools that map to independent HTML app resources.

MCP Server for Apache Pinot

Provides advanced charting widgets (uPlot time series, ECharts box plots and parallel coordinates) for Urano Desktop/Cloud via MCP tools that build uiSpec JSON for rendering.

Enables natural-language questioning of CSV datasets by loading tables, listing columns, computing aggregates, suggesting ECharts visualizations, and returning grounded voice-style answers through MCP tools.

A Model Context Protocol server that connects AI agents to Apache Jena, enabling them to execute SPARQL queries and updates against RDF data stored in Jena Fuseki.

Enables generation of various chart types (bar, line, pie, scatter, radar, heatmap, and more) using ECharts library, returning preview URLs to visualize data through natural language requests.

Enables AI agents to manage and interact with Apache AGE graph databases through natural language. Supports creating, updating, querying, and visualizing multiple graphs with vertices and edges.

Enables AI-controlled management of Apache Beam data pipelines across different runners (Flink, Spark, Dataflow, Direct) via the Model Context Protocol.

Provides integration with Apache Airflow's REST API, allowing AI assistants to programmatically interact with Airflow workflows, monitor DAG runs, and manage tasks.

Offline MCP server that checks and scans your own AI prompts and outputs against a local compliance rule corpus. Returns rule ID, severity, citation, and remediation per finding — no API key, Apache 2.0.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.

Provides full-text search and retrieval tools for Apache Spark documentation using SQLite FTS5 with BM25 ranking. It enables AI assistants to efficiently search, filter by section, and read specific Spark documentation pages.

Open-source mind maps and whiteboard your agent draws on live: 22 tools for mind maps, notes, shapes, tables, charts, connectors, comments and HTML/PDF export; boards are local files.