How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
[BETA — v2 rebuild] MCP server for data analytics — Shopify, Stripe, CSV, forecasting, ML. Works in Claude, Cursor, and any MCP client. Expect rough edges while the rewrite lands.
The main features of embeddedlayers/mcp-analytics are: Customer Data Platforms.
Open-source alternatives to embeddedlayers/mcp-analytics include: azmartone67/dchub-mcp-server — Data-center intelligence MCP server — 38 tools, 21,000+ data-center facilities (170+ countries), 232 US power markets… ckalima/pipedrive-mcp-server — MCP server for Pipedrive CRM. 155 contract-tested tools, v2-first API, gated destructive ops. Works with Claude… hustcc/mcp-echarts — 🧬 Generate visual charts using ECharts with AI MCP dynamically, used for chart generation and data analysis. hustcc/mcp-mermaid — ❤️ Generate mermaid diagram and chart with AI MCP dynamically. iaptic/mcp-server-iaptic — Model Context Protocol server for interacting with iaptic. antvis/mcp-server-chart — This project is a Model Context Protocol server that enables large language models to generate and render data…
Data-center intelligence MCP server — 38 tools, 21,000+ data-center facilities (170+ countries), 232 US power markets (DC Hub Power Index), 2,000+ tracked M&A deals, ISO grid telemetry, fiber & energy pricing. Free to cite (CC-BY-4.0).
MCP server for Pipedrive CRM. 155 contract-tested tools, v2-first API, gated destructive ops. Works with Claude Desktop, Claude Code, and any MCP client.
🧬 Generate visual charts using ECharts with AI MCP dynamically, used for chart generation and data analysis.
This project is a Model Context Protocol server that enables large language models to generate and render data visualizations, charts, and diagrams. It functions as a toolset for AI assistants to transform raw data into professional visual representations. The server utilizes an intelligent selection layer to determine the most effective visualization format based on the provided data. It supports remote rendering via external HTTP services and provides the flexibility to route requests to self-hosted rendering endpoints for private network environments. Capabilities cover a wide range of da