"Building a Real-Time Automated DNS and AI Load Balancing System with AWS Integration" matching MCP servers:

Enables MCP clients to load a ledger from an object, file path, or JSON text and inspect it as a local numeric timeline with tracks and overlapping blocks, and to open the visualization in a browser.

Analyzes traffic patterns throughout the day using Google Maps API and provides visual insights and recommendations for optimal commute times.

| 地価トレンド予測 | 新宿区の5年後地価をAI予測。CAGR・投資シグナル付き | | 企業立地需要分析 | 名古屋市中区のオフィス・工場需要スコアを算出 | | ファミリー向け適性評価 | 横浜市西区の教育・安全・医療スコアを総合評価 | | ポートフォリオ最適化 | 東京・大阪・埼玉の3エリアに投資配分を最適化 | | What-If シナリオ分析 | 大阪市中央区で新駅開設シナリオを試算 | | 店舗出店適地評価 | 福岡市博多区の人流・商業施設・交通データで出店適性を判定 |

An unofficial MCP server for generating infographics and visuals from text using the Napkin AI API, enabling AI assistants to create professional diagrams, mindmaps, and charts.

MCP server for AI-driven CAD operations, enabling parametric modeling, build, inspection, measurement, rendering, and diff comparison with STEP, DXF, and GLB export.

Enables AI-native statistical analysis and reproducible research workflows through MCP, including natural language planning, protocol-based analysis, Python/R cross-validation, and publication-ready figure generation.

MCP server for A-share stock technical analysis and AI prediction, enabling LLM-based interaction to analyze stocks.

Enables controlling Power BI with AI through natural language commands for creating DAX measures, explaining metrics, suggesting KPIs, and organizing models.

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.

Enables AI hosts to generate and open Mermaid diagram links in Markdown files, providing tools for syncing, listing, and injecting diagrams via the Mermaid.ai editor.

Enables AI clients to generate over 26 chart types via MCP, automatically starting a private rendering service.

Enables users to create, validate, view, and export system stock-and-flow maps from a versioned JSON model through MCP-capable hosts over local stdio or hosted Streamable HTTP. Supports causal-loop and nested-level mapping while keeping submitted model content with the caller and requiring no LLM provider key.

Enables asking natural-language questions about WHOOP recovery, sleep, HRV, strain, and workouts inside Claude, Codex, and GitHub Copilot. Provides read-only tools, resources, and prompts for personal health analytics, along with HYROX and triathlon tracking and a local chart-first dashboard.

Enables generating Power BI .pbit dashboards from CSV files or live SQL databases using plain-English prompts and optional reference-image layouts, with local-only processing and MCP tools for Claude Desktop.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through MCP protocol.

Enables Codex to control a Gephi 3D network view through natural language, including network generation, 3D layout, node focus and neighbor highlighting, layered views, and PNG/PDF export.

Enables creating surveys, validating questions, collecting responses, and generating analysis reports.

A local, fully vectorized computational engine for stock market analysis that enables AI to perform factor calculation, strategy backtesting, IC analysis, and GPU-based multi-dimensional visualization using local DuckDB data.

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 natural-language queries about sales metrics, returning interactive charts inline in chat via MCP Apps with a markdown fallback for unsupported hosts.

MCP server that lets Claude, Cursor, or any MCP-compatible client drive Sheepit projects — enabling campaign management, destination configuration, dashboard creation, and insights queries directly from a chat interface.

Enables interactive learning and visualization of Binary Search Trees and AVL Trees through operations like insertion, deletion, and tree traversal, with real-time balancing rotations.

MCP server that provides F1 telemetry analysis, tyre degradation modeling, and pit strategy recommendations, delivering race engineer-style calls grounded in real data. It exposes tools for degradation fits, fuel correction, and strategy reasoning via LangGraph.

Enables AI assistants to generate and render individual and composite Human Design charts, explore authorized chart and library data, and manage account usage and Website Builder projects with secure OAuth and entitlement filtering.

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

Enables users to prepare and validate market data, launch and control backtests, and retrieve results, causal explanations, and self-contained reports through stdio tools. It also supports polling or canceling jobs and running sweep, walk-forward, factor, and study research workflows with bounded pagination and reproducible artifacts.

Opens, inspects, and renders DXF/CAD drawings for AI agents: describe_dxf returns structured facts (layers with actual drawn colors, units, bounds, text content) and render_dxf returns PNG images. On MCP Apps hosts like ChatGPT and Claude, view_dxf opens an interactive in-chat viewer with pan, zoom, and layer toggles.

Converts plain-English stock requests (e.g. "compare Apple and Microsoft YTD") into validated yfinance/matplotlib scripts, AST-checked and executed in a sandbox to produce chart PNGs. Exposes parsing, saving, execution, and history-listing tools to Claude Desktop and Claude Code through FastMCP, backed by local Ollama/DeepSeek-R1 or cloud Groq/GPT-4o models.

An HTTP MCP server for exploring CSV files that masks PII before any code execution, enabling safe data analysis with local or cloud LLMs.

Enables AI assistants to authenticate against a cloud geospatial analysis platform, search and inspect its datasets, render them as maps, and compute statistics over specified regions. It exposes these capabilities as MCP tools that can be dropped into any Next.js project via a route-based adapter.