"Setting up Minecraft (MCP) servers with Python and Visual Studio Code" matching MCP servers:

An AI-driven data visualization and SQL chat platform that enables natural language to SQL conversion, interactive chart generation, and database querying through a comprehensive MCP interface. Supports multiple databases, intelligent chart recommendations, and secure data management with temporary link sharing.

This server enables agents to identify users and organizations, inspect versioned datasets and model lineage, start training jobs, run and read evaluations, verify deployments, and execute typed workflows through authenticated MCP endpoints.

Enables LLMs to query live data from over 250+ sources via CData Python Connectors using natural language. Wraps connectors as a Model Context Protocol server.

Integrates with the Datalog Studio REST API to explore projects, tables, and assets within a workspace. It enables users to understand data schemas and upload plain text content directly for AI processing.

Label Studio MCP Server

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

An MCP server that enables retrieval of historical weather data (temperature, precipitation, conditions, etc.) from Visual Crossing for specified locations and dates.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

A resilient MCP server wrapping FiinQuant/FiinQuantX Python SDK for Claude Desktop and Cursor, providing market data, fundamental analysis, screening, and technical indicators via stdio with timeouts, error envelopes, and free-tier guards.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

A cryptocurrency price service that provides real-time crypto pricing information through an MCP (Model Context Protocol) framework with CoinMarketCap API integration.

Enables AI assistants to load CSV datasets, compute summary statistics, filter rows, rank columns, and compute correlations through the Model Context Protocol.

A read-only MCP server that connects AI clients to your own bank, credit card, loan, and brokerage data through Plaid or Teller, letting you query accounts, balances, transactions, holdings, liabilities, identity, income, and run debt avalanche/snowball payoff analysis. Credentials and access tokens stay locally in a chmod-600 SQLite file, with outbound calls limited to the provider's API.

MCP server providing seamless integration with Trino and Iceberg for advanced data exploration, querying, and table maintenance.

Enables MCP-based access to a US stock data warehouse and screener, allowing automated screening with daily free market data.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.

Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.