This MCP server leverages AntV to generate over 25 types of charts and spreadsheets, facilitating data visualization and analysis directly within AI-assisted development environments. It's ideal for developers needing to quickly visualize data or explore relationships without leaving their coding workflow.

This MCP server integrates with VictoriaMetrics APIs and its documentation, offering a comprehensive interface for monitoring, observability, and debugging tasks. It is ideal for engineers and tools seeking advanced automation and interaction capabilities with their VictoriaMetrics instances.

This MCP server provides a suite of tools for in-depth analysis of Instagram engagement, allowing users to extract sentiment from comments, compare account metrics, and gain demographic insights. It's ideal for marketers and businesses seeking to understand their audience better and identify potential leads directly from Instagram data.

This Claude Code skill automates the creation of detailed e-commerce business reviews from raw order transaction CSV data. It performs KPI decomposition, identifies trends across 30d, 90d, and 365d horizons, and generates a REVIEW.md document. The report includes an executive summary, multi-horizon dashboard, KPI trees with health signals (🔴/🟢), structured findings (what/why/what to do), and a prioritized action plan with deadlines. It's ideal for D2C owners, marketers, and analysts needing quick, insightful performance reports.

This Model Context Protocol (MCP) server integrates GreptimeDB, an open-source observability database, with AI assistants. It provides a rich set of tools for executing SQL, TQL (PromQL-compatible), and time-window RANGE queries. Developers can manage data pipelines and Perses dashboards directly. Key features include robust security with read-only enforcement, data masking for sensitive information, and comprehensive audit logging. It also offers built-in prompt templates for common tasks like metrics analysis, log processing, and IoT monitoring, streamlining AI-driven data exploration and m