Zaturn

MCP Server for Data Exploration enables users to interactively explore and analyze complex datasets using prompt templates and tools within the Model Context Protocol ecosystem. Designed as a personal Data Scientist assistant, it facilitates the conversion of raw data into actionable insights without manual intervention. Users can load CSV datasets, run Python scripts, and generate tailored reports and visualizations through an AI-powered interface. The server integrates directly with Claude Desktop, supporting rapid setup and seamless usage for both macOS and Windows.

• ⭐ 503
• MCP
• reading-plus-ai/mcp-server-data-exploration

MCP Database Utilities provides a secure, standardized service for AI systems to access and analyze databases like SQLite, MySQL, and PostgreSQL using a unified YAML-based configuration. It enforces strict read-only operations, local processing, and credential protection to ensure data privacy and integrity. The tool is suitable for entities focused on data privacy and minimizes risks by isolating database connections and masking sensitive data. Designed for easy integration, it supports multiple installation options and advanced capabilities such as schema analysis and table browsing.

• ⭐ 85
• MCP
• donghao1393/mcp-dbutils

MXCP is an enterprise-ready framework that implements the Model Context Protocol (MCP) for building secure, production-grade AI application servers. It introduces a structured methodology focused on data modeling, robust service design, policy enforcement, and comprehensive testing, integrated with strong security and audit capabilities. The framework enables rapid development and deployment of AI tools, supporting both SQL and Python environments, with built-in telemetry and drift detection for reliability and compliance.

• ⭐ 49
• MCP
• raw-labs/mxcp

GIS MCP Server provides a Model Context Protocol (MCP) server implementation that enables Large Language Models to access and perform sophisticated GIS operations. It bridges AI assistants with Python geospatial libraries such as Shapely, GeoPandas, PyProj, Rasterio, and PySAL. The server supports a wide range of spatial analysis, coordinate transformations, raster and vector data processing, and geospatial intelligence tasks. By integrating with MCP-compatible clients, it enhances AI tools with precise and extensible spatial capabilities.

• ⭐ 70
• MCP
• mahdin75/gis-mcp

VictoriaMetrics MCP Server implements the Model Context Protocol (MCP) to provide seamless integration with VictoriaMetrics, allowing advanced monitoring, data exploration, and observability. It offers access to almost all read-only APIs, as well as embedded documentation for offline usage. The server facilitates comprehensive metric querying, cardinality analysis, alert and rule testing, and automation capabilities for engineers and tools.

• ⭐ 87
• MCP
• VictoriaMetrics-Community/mcp-victoriametrics

Signoz MCP Server acts as a bridge between SigNoz observability platforms and AI assistants by implementing the Model Context Protocol (MCP). It exposes a suite of tools for querying dashboard information, fetching panel and metrics data, executing custom queries, and retrieving traces or logs from SigNoz. The tool supports integration with popular AI assistants, flexible deployment options (Docker, local virtual environments), and secure configuration via environment variables or YAML files. The server is designed to enable standardized programmatic context retrieval for enhancing AI/LLM workflows.

• ⭐ 11
• MCP
• DrDroidLab/signoz-mcp-server