"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.

MCP ECharts is a dynamic chart generation and data analysis tool based on Apache ECharts, supporting multiple export formats and MinIO object storage integration.

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.

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

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.

A proof of concept MCP server for Apache OFBiz

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.

A Model Context Protocol server enabling Claude to maintain user context through Apache Unomi profile management.

An MCP server that enables AI agents to query RevenueCat's subscription analytics API using natural language, retrieving metrics like MRR, churn, and revenue.

The accountability layer for AI agents — a named human's signed yes before an agent does anything irreversible (payment, record change, deploy), then an offline-verifiable Trust Receipt. Apache-2.0, formally verified.

Sovereign, encrypted, persistent memory for AI agents. Eight MCP tools — remember, recall, forget (GDPR Art. 17 erasure), share, governance. Anchored on COTI V2 mainnet. Apache-2.0.

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.

An MCP server that converts Apache Airflow DAGs into Prefect flows. It provides tools to read DAGs, lookup translation knowledge, validate code, search Prefect docs, scaffold projects, deploy, and generate migration reports.

Automates the full setup and deployment of Ballerina + Apache ActiveMQ integrations inside a WSO2 Integrator workspace, from broker validation to a runnable BI-low-code-ready project.

Agent-native hosting: your agent deploys any folder to a live URL in one command — no account, no dashboard, no CAPTCHA — and hands the human a link plus a plain-language summary. Full deploy lifecycle as MCP tools (deploy, verify, logs, inspect, rollback), production approval human-only; static sites and full Node.js apps, open source (Apache-2.0).