"Information about RDKit (chemistry software toolkit)" matching MCP servers:

AI-powered data visualization MCP server that generates publication-ready charts from natural language descriptions while keeping data local.

Renders Mermaid diagram markup to PNG images using Puppeteer/Chromium. Enables AI-generated diagrams to be previewed inline and saved to disk.

Enables ChatGPT to answer ordinary chemistry questions by calling local RDKit tools that draw molecules inline, rotate them in 3D, and report stereochemistry, IUPAC numbering and lone pairs. Also resolves molecule names, enumerates stereoisomers, and finds substructure matches.

Embeds live, interactive Tableau dashboards in ChatGPT, pushing mark selections to the model so questions about specific data points are answered with live queried numbers.

Enables querying Tableau lineage through the Metadata API via MCP, supporting impact analysis, where-used lookups, and content search. Provides read-only tools for answering natural-language questions about workbooks, datasources, fields, and dependencies.

MCP server for AI Diagram Maker — generate software engineering diagrams from natural language, code, ASCII diagram, images, or Mermaid. Inline diagram rendering using MCP apps UI and diagram URL in responses. Works with Cursor, Claude Desktop, Claude Code, and any MCP-compatible AI.

Provides AI agents with a TradingView-centric toolkit for screener queries, historical FX data, pattern scanning, chart rendering, backtesting, Pine tooling, and optional account/desktop integration.

Enables natural-language interaction with Ladybug Tools for building performance simulation, 3D modeling, and data visualization, allowing agents to perform complex environmental analysis tasks without CAD software.

A comprehensive MCP server that provides complete access to Qlik Sense applications and their detailed information for AI assistants and other MCP clients.

An MCP server that provides an LLM with access to R's statistical toolkit including hypothesis tests, regression, psychometrics, survival analysis, time series, and plots through a persistent R session.

twilize is a Model Context Protocol (MCP) server and Python toolkit for generating Tableau Desktop workbook files (.twb / .twbx) from code or AI-driven tool calls

Enables AI assistants to create, edit, and export IFC5/IFCX building information models through natural language, handling spatial structure, elements, geometry, metadata, validation, and export.

Exposes a broad mathematics toolkit including symbolic algebra, calculus, numerical methods, linear algebra, statistics, discrete math, graph theory, rendering, and optional GPU acceleration via MCP tools for use with Claude Desktop and other MCP hosts.

Enables transforming grounded AI answers into interactive information views such as comparisons, plans, checklists, timelines, and decision views, while preserving a plain-language fallback.

Enables natural-language queries about disk usage by driving WizTree scans and analyzing cached CSV snapshots. Users can find large files, duplicate data, folder breakdowns, and more without repeatedly rescanning the disk.

Enables users to ask questions about self-hosted or Cloud Umami Analytics through a secure, model-friendly Model Context Protocol interface, with read-only tools for traffic, conversions, revenue, sessions, events, reports, and performance investigations.

Bridges AI assistants to seismology software (ObsPy, CWP/SU, SAC, PyGMT), allowing users to process seismic waveforms and perform analysis through natural language instead of writing code.

Enables visualizing GeoJSON data on an interactive map directly in Claude Desktop, allowing users to request maps of information found or generated.

MCP (Model Context Protocol) server that exposes the okama investment portfolio toolkit to AI assistants — Claude Desktop, Claude Code, Cursor, Codex, and any other MCP-compatible client.

Provides a local-first chemistry workbench for AI agents, enabling SMILES validation with human-readable diagnostics, molecule drawing, property calculation, format conversion, standardization, and batch cleaning via MCP.