"Answer Engine Optimization (AEO) Audit Guide" matching MCP servers:

Enables auditing chart color palettes for colorblindness accessibility by simulating CVD and measuring contrast. Provides tools to audit palettes and design tokens mid-conversation.

Enables local offline machine learning workflows, including CSV profiling and cleaning, classifier and neural network training, hyperparameter optimization, evaluation metrics, confusion matrix plots, Streamlit dashboards, and HTML reports through MCP tools.

Enables natural-language-driven analytics over CSV/Parquet or built-in data by decomposing questions into analytical tasks, running them via deterministic DuckDB and SciPy tools, and publishing only claims verified against the underlying rows.

A statistical analysis MCP server offering 30 tools for descriptive statistics, hypothesis tests, regression, and time series, all returning Markdown reports with automatic interpretations to enable AI agents to perform comprehensive data analysis.

A graph database MCP server that lets AI assistants build, analyze, and visualize relationship graphs with algorithms like PageRank and cycle detection.

Audits local Tableau workbooks for unused assets, duplicate worksheets, and dashboard weight, providing cleanup reports and health summaries.

Enables AI agents to perform Black-Litterman portfolio optimization with investor views, backtesting, and asset analysis, generating dashboards for visualization.

Enables AI agents to perform deterministic search synthesis and compile Sparkpage layouts into comparison matrices and ready-to-render HTML interfaces through a zero-dependency Python MCP server. Plugs into Claude Desktop, Cursor, and other MCP clients for structured, low-latency output with execution telemetry.

Enables AI agents to perform dynamic search synthesis and compile Sparkpage layouts into comparison matrices and HTML interfaces, running deterministically with zero external dependencies over the Model Context Protocol.

Enables conversational spatial SQL queries in plain English, turning natural language questions into validated PostGIS operations and rendering results as GeoJSON on an interactive map.

Enables AI assistants to read and modify Power BI Desktop files programmatically, including querying models, creating measures, and managing relationships through natural language.

A high-performance MCP server that connects AI agents to premium computational tools for genetic algorithm optimization and data visualization, with automated USDC microtransactions via the x402 protocol.

Geneva MCP brings production-grade forecasting directly into AI assistants and coding agents. Connect any MCP-compatible client to the Geneva Forecasting Engine and run rigorous time series forecasts through natural conversation.

AI e-commerce operations manager for MCP. Inventory forecasting, pricing optimization, RFM customer segmentation, order anomaly detection, and automated reports for Shopify and WooCommerce.

Exposes a time series forecasting model as an MCP tool with built-in audit logging for every call, enabling trustworthy autonomous forecasting.

An MCP server that connects AI assistants to a local Wolfram Engine, enabling symbolic math, numerical analysis, and data visualization through Wolfram Language. It provides secure expression filtering, client authentication, and supports both local stdio and HTTP transports.

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.

Enables managing Splitwise expenses and generating premium spending analytics with category breakdowns, trends, and settlement optimization through natural language.

Integrates with Google Search Console to enable querying search analytics, comparing performance periods, generating visual reports, and identifying SEO optimization opportunities through natural language.

Viznoir empowers AI agents to directly analyze and visualize complex 3D scientific and engineering data in cinematic resolution using a fully headless VTK engine. It enables LLMs to seamlessly execute advanced physical analysis, 3D rendering, and generate publication-ready animations purely through natural language commands.