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    Renders word-sized charts — sparklines, bars, bullets and 100+ more types — to self-contained SVG with generated alt text, small enough to sit inline in a model's reply or a table cell. Three tools: find the right chart for a question, get its wiring, and render it.
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    MIT
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    Renders OHLCV data as candlestick chart PNGs and returns inline images. It is a pure renderer with no network access, allowing models to view charts generated from provided data.
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    Turns a CSV — or a public dataset named in plain English — into an animated chart video. Every numeric claim in the generated narration is recomputed from the source rows before export, and a claim that does not reconcile blocks the export rather than shipping.
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    MIT
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    Data-visualization MCP server for ROOT Workspace. It enables creating and iterating on charts (Vega-Lite, Python plots) with a persistent kernel and vision loop.
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    diagramzu-mcp lets an AI client (Claude, Cursor, ChatGPT, etc.) author Mermaid diagrams in a shared workspace that a team can read, comment on, embed, and present at a clean URL — rather than just generating a one-off diagram. Hosted endpoint https://mcp.diagramzu.ai/mcp or local npx -y @diagramzu/mcp. Also listed in the official MCP registry as ai.diagramzu/mcp.
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    MIT
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    A Model Context Protocol (MCP) server that exposes tools for exploring and querying SQLite and PostgreSQL databases. It allows Large Language Models (LLMs) to inspect table structures, perform statistical profiling, generate entity-relationship diagrams, and execute queries safely.
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    MIT
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    An MCP server that enables LLMs to create and open diagrams in draw.io using XML, Mermaid, or CSV formats, by building a URL with compressed content and opening it in the browser.
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    MIT
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    A read-only, cross-platform visualization layer for Cortex that renders memory, sessions, and code into six live reading angles (graph galaxy, 3D anatomical brain, execution trace, consolidation board, knowledge browser, and wiki) without ever writing a memory.
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    MIT
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    Enables to interact with Felt maps programmatically through an MCP server. Supports listing, retrieving details, and creating maps with natural language.
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    MIT
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    Exposes ASCIIFlow drawing primitives as tools to enable AI assistants to generate ASCII wireframes and diagrams from natural language descriptions. It provides commands for creating canvases and drawing boxes, lines, arrows, and text using a character-grid coordinate system.
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    Enables Magic: The Gathering players to analyze deck lists using real Scryfall oracle text, detecting synergies and conflicts. Generates three viewable documents: an interactive synergy map, a detailed guide, and a printable cheat sheet.
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    MIT