"Information about ECharts - a data visualization library" matching MCP servers:

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

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 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.

Enables coding agents to establish exact-release library identity, search provenance-tracked API, docs, example, source, and release evidence, compare releases, and test proposed invocations in isolated capsules for Rust and Python dependency environments.

An MCP server that allows AI models to create data visualizations using Vega-Lite syntax by providing tools to save data tables and generate visualizations from them.

Enables AI agents to manage Cloudera Data Visualization resources including groups, users, roles, segments, workspaces, datasets, visuals, connections, and migrations via natural language.

Enables AI-assisted development by providing a library of 110+ curated prompts, workflows, and coding standards, with MCP tools for prompt retrieval, composition, and multi-step workflow chains.

Enables automatically generating standalone MCP servers from any Python library, exposing its functions as deterministic callable tools.

An MCP server that enables users to manage, search, and apply specialized AI personas within Claude Desktop and Claude Code CLI. It features a local-first architecture with YAML-based storage for organizing curated prompts and role collections.

Serves Markdown skill and rule files from a local directory to AI agents on demand, letting them list and fetch specific instructions without context bloat.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

An MCP server that scans React and Vue projects, extracts component metadata (props, slots, events, imports, usage), and exposes it to AI coding agents via structured tools.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

MCP server generated from an OpenAPI Specification, exposing tools via HTTP. It allows clients to invoke API operations using JSON-RPC 2.0 requests.

Enables data engineers and BI professionals to perform data pipeline development, quality assurance, visualization, and API integration locally with AI assistance.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Provides AI assistants with access to design documentation across multiple code libraries, enabling discovery of existing utilities and patterns to avoid reimplementation.

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

A comprehensive prompt library for frontend developers covering React, frontend best practices, and coding guidelines, accessible via MCP tools.

Search and retrieve Google Apps Script libraries with AI-generated summaries and usage examples directly from MCP clients.