"A server for trading items on Minecraft MCP servers" matching MCP servers:

Enables AI agents to log trades from chart screenshots, validate them against custom strategy rules, import statements from MT5/TradingView and other brokers, and review R-based statistics in a local dashboard.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Provides aerodynamic analysis tools through MCP, enabling geometry generation, meshing, CFD solving, and visualization for 2D airfoils.

A clean-room SHARP-on-MCP compliant FHIR R4 MCP server that enables AI agents to interact with any FHIR R4 endpoint using SHARP context headers, without server-side OAuth. It provides clinical tools, lab results, imaging, and interactive MCP-UI dashboards.

A production-grade MCP server that provides tools to fetch historical stock data, company information, and technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands) via yfinance, and includes a Flask web dashboard for visual analysis.

Enables your own ChatGPT to build and manage a collaborative work board—dashboards, categories, datasets, monitors, and policies—through typed WebMCP tools, with human approval, audit trails, and guardrails enforced on every action.

Enables Claude to read a project's FastStats metrics and then design, validate against real data, and publish charts, dashboards, event markers, and custom data sources. Every write is previewed and dry-run first, with read-only mode and confirmation guards for destructive actions.

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 AI assistants to drive a live TradingView chart in Chrome, turning natural-language trading ideas into compiled Pine Script indicators, adding them to charts, and reading back results. It also supports chart navigation, indicator management, screenshots, and strategy tester backtest results.

Enables AI assistants to control a logged-in TradingView chart in Chrome, including writing and compiling Pine Script indicators, adding them to charts, changing symbols and timeframes, capturing screenshots, and retrieving strategy tester results.

Google Search Console for Claude and other MCP clients. Sign in with Google in one click, then ask about clicks, queries, rankings and indexing, export every GSC report as CSV (beyond the 1,000-row UI limit), inspect URLs, submit sitemaps and verify sites. Includes a local SEO dashboard. Free, open source, runs on your computer.

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

MCP server for Microsoft Power BI and Fabric, enabling Claude to discover workspaces, semantic models, generate and execute DAX queries, and retrieve report metadata via device-code authentication.

MCP server providing data analytics tools for AI agents to load, clean, analyze data, generate charts and dashboards.

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.

Calculates Taiyi Shenshu (太乙神數) based on a given datetime and returns structured text and a board PNG image.

Zero-dependency charts for Python and AI agents. SVG and PNG, 15 chart types, a one-line MCP server, and a Claude skill.

Open-source mind maps and whiteboard your agent draws on live: 22 tools for mind maps, notes, shapes, tables, charts, connectors, comments and HTML/PDF export; boards are local files.

Enables exploratory data analysis and machine learning on CSV datasets with tools for profiling, missing values, correlation, plotting, model training, and prediction.