30 open-source projects similar to isaacwasserman/mcp-vegalite-server, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.
Beautiful diff visualization for Claude Desktop. Transform code diffs into stunning visual comparisons with GitHub Gist integration and local file output.
This project is a Model Context Protocol server that enables large language models to generate and render data visualizations, charts, and diagrams. It functions as a toolset for AI assistants to transform raw data into professional visual representations. The server utilizes an intelligent selection layer to determine the most effective visualization format based on the provided data. It supports remote rendering via external HTTP services and provides the flexibility to route requests to self-hosted rendering endpoints for private network environments. Capabilities cover a wide range of da
🧬 Generate visual charts using ECharts with AI MCP dynamically, used for chart generation and data analysis.
❤️ Generate mermaid diagram and chart with AI MCP dynamically.
:bar_chart: Create beautiful, responsive, animated charts using a simple and intuitive API.
This project is a declarative data visualization library that provides a composable suite of user interface components for rendering interactive charts. It functions as an SVG-based charting engine, allowing developers to construct complex visualizations by nesting modular building blocks such as axes, grids, legends, and data series within a unified layout. The library distinguishes itself through a highly responsive architecture that automatically reconciles layout changes and maps data domains to pixel coordinates using mathematical scale functions. It prioritizes performance through memoi
A grammar of data visualization and Flutter charting library.
Perspective is a columnar data analytics library and streaming data visualization engine. It provides an interactive data grid component and notebook analytics widgets designed for processing high-volume data and rendering interactive charts and grids. The system utilizes a high-performance query engine to enable real-time data analysis and streaming dataset visualization. It supports the creation of customizable dashboards and reports that update automatically as new data arrives without requiring full dataset reloads. The project covers large-scale dataset analytics through a schema-driven
Hellocharts-android is a data visualization library and charting framework for Android applications. It provides a collection of custom view components used to render datasets as visual elements, such as line, column, and pie charts. The library supports interactive visualizations that allow users to navigate data through touch gestures, including pinching, scrolling, and panning. It also includes built-in capabilities for animating data points and chart elements to create smooth visual transitions during dataset updates. The framework covers a broad range of visualization needs, including c
A beautiful bezier line chart widget for flutter that is highly interactive and configurable.
WilliamChart is an Android data visualization library and toolkit used to render interactive charts and graphs within Android applications. It functions as a UI component library for integrating data-driven dashboards and metrics into Android layouts. The library includes a specialized component for representing proportional categorical data as donut charts, which are circular charts with hollow centers. It provides a drawing engine that uses low-level APIs to map numerical data to pixel coordinates on the screen.
Elegant OHLC Candlestick and Trade Volume charts for @Flutter
MPAndroidChart is an Android charting library and data visualization framework that provides a set of reusable view components for rendering statistical data. It enables the display of numerical datasets through various chart types, including line, bar, pie, radar, bubble, and candlestick charts. The library focuses on an interactive graphing workflow, allowing users to explore complex data sets through scaling, panning, and animations. It includes specific support for financial charting to track market trends and price movements, as well as tools for building mobile dashboards.
metrics-graphics is a data visualization library and declarative graphics framework designed to create principled data graphics and layouts. It functions as a statistical graphics engine that maps raw data to geometric shapes and structured objects to render complex, data-driven layouts. The toolkit specializes in rendering time-series data through line charts and scatterplots using a consistent layout system. It also provides capabilities for statistical distribution mapping, including the creation of rug plots to represent one-dimensional data density. The system covers a broad surface of
ECharts is a JavaScript data visualization library and web charting framework used to render interactive 2D and 3D data plots within a web browser. It functions as a visualization engine that transforms raw data into customizable charts and graphs. The project includes a WebGL-based hardware acceleration engine specifically for producing three-dimensional plots and globe visualizations. This allows the library to handle large and complex datasets through GPU-accelerated rendering. The framework supports both canvas-based raster rendering and SVG-based vector rendering. It provides capabiliti
This repository serves as an educational collection of interactive notebooks and code examples designed to demonstrate fundamental machine learning and deep learning concepts. It provides a structured environment for exploring data science workflows, ranging from basic numerical computing and statistical analysis to the construction of complex neural network architectures. The project distinguishes itself through a focus on hands-on experimentation, offering practical implementations for tasks such as computer vision, natural language processing, and statistical simulation. Users can engage w
This repository is a comprehensive collection of instructional guides and practical examples for Python development, focusing on machine learning, data science, and web scraping. It provides implementations for neural networks, reinforcement learning algorithms, and deep learning architectures using PyTorch, alongside detailed manuals for scientific computing and data visualization. The project distinguishes itself by offering specialized tutorials on concurrent programming to optimize CPU performance and guides for setting up Linux development environments. It covers the implementation of ad
This project is a collection of educational notes and tutorials focused on Python programming, scientific computing, and data analysis. It serves as a reference for learning language basics, advanced techniques, and object-oriented design. The materials include implementation guides for building linear, logistic, and convolutional neural networks using symbolic graph frameworks. It also provides instruction on manipulating and visualizing structured data frames and performing complex mathematical operations through numerical libraries. The repository includes a system for converting interact
This project provides a suite of interfaces and tools for accessing electricity carbon intensity and production metrics. It includes an API for real-time and historical data, a geographic power data map for visualizing regional carbon intensity and renewable energy percentages, and a system for extracting datasets required for standardized greenhouse gas emissions reporting. The project features an interactive API sandbox that allows users to test requests and inspect data responses without writing code. It also includes mechanisms for institutional email verification to manage access to hist
This project is a collection of educational resources and reference implementations for neural network development using TensorFlow. It serves as a comprehensive learning course, machine learning curriculum, and practical implementation guide for building deep learning architectures. The codebase provides instructional materials and examples covering a wide range of model types, including convolutional neural networks for image classification, recurrent networks and long short-term memory cells for sequential data, and autoencoders for generative modeling. It also includes implementations for
This project is a comprehensive technical reference and programming cheatsheet for the Python language. It serves as a curated catalog of language features, syntax patterns, and standard library functions designed to help developers identify and apply correct coding patterns. The documentation covers a broad range of functional areas, including language fundamentals such as object-oriented structuring, functional logic, and list comprehensions. It also provides guidance on utilizing the standard library for data analysis, file management, networking, and concurrent execution. The reference e
The newest, fastest, and most advanced amCharts charting library for JavaScript and TypeScript apps.
Altair is a declarative data visualization library for Python based on the Vega-Lite grammar. It allows users to create statistical visualizations by mapping data fields to visual properties rather than writing imperative drawing code. The library focuses on interactive charting through a system of linked selections and filters that update multiple visualizations based on user input. It renders charts as JSON and HTML for display in web browsers and interactive notebooks. The project covers statistical data analysis and interactive data exploration, providing capabilities to export visuals a
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.