Official description7 sourcesMCP servers8d ago
embeddedlayers/mcp-analytics
The statistical analyst in your AI chat — bring data and a question, own a citable, re-runnable analysis. Four depth tiers, from instant Snapshot to full Deck study. Works in Claude, Cursor, and any MCP client.
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Config template (adjust for your client)
claude mcp add mcp-analytics -- npx -y mcp-analytics
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
- Star count
- 8 ★ · embeddedlayers/mcp-analytics · read from the repository page · (checked 2026-10-16 20:00:20)
- Source
- collected from the punkpeye/awesome-mcp-servers list · type: MCP server
- Harvest history
- first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
- Score
- score 703 · 8 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository
embeddedlayers/mcp-analytics；first catalogued 2026-10-09；last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.Third-party quality signals
MCP Analytics
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
**A statistical analyst in your AI chat.** Bring a dataset and a question, get back a citable, re-runnable report with its method named.
MCP Analytics is a Model Context Protocol server that answers business and statistical questions about your data, as deep as each question needs:
- **Answer:** a quick question about the data, read from all of it, shown with how we got it, and saved.
- **Analytics:** a tested statistical method runs on the data, and we interpret it with charts and a written report.
- **Custom Analytics:** a question only your business asks, built for your data from proven models, yours to re-run on next month's file.
Intelligent routing picks the depth: you describe the question, and the server says which path answers it and why. Analytics is repeatable: same data, same numbers. Every report names its method and the code that ran it, and runs again on new data.
It is for business and statistical questions about data, not a general-purpose assistant.
Website: mcpanalytics.ai · Free tools you can try in the browser: mcpanalytics.ai/free
Connect
**Endpoint:** https://api.mcpanalytics.ai/mcp/api-key (Streamable HTTP, JSON-RPC)
**Authentication:** an API key in the X-API-Key header. Create an account at mcpanalytics.ai and copy your key from your account settings.
**Claude Code:**
**Browse before you sign up.** Without a key the server answers in discovery mode: you can connect and list the tools, but not run anything.
Start
Ask your AI assistant a question about your data, for example:
- "Upload sales.csv. What changed in revenue from May to June, and which channel drove it?"
- "Which customers are most likely to churn?"
- "Forecast next quarter's sales from this file."
The first call is the resolver: it reads your question and your data, executes nothing and charges nothing, and names the path that answers it (an answer, a library analysis, or a custom build) with the reason. Then it runs that path.
What you get
- A report with charts, tables and a written interpretation, with its method named and the code that ran it.
- Re-runs on new data: run the same analysis on next month's file.
MCP Analytics is a Model Context Protocol server that answers business and statistical questions about your data, as deep as each question needs:
- **Answer:** a quick question about the data, read from all of it, shown with how we got it, and saved.
- **Analytics:** a tested statistical method runs on the data, and we interpret it with charts and a written report.
- **Custom Analytics:** a question only your business asks, built for your data from proven models, yours to re-run on next month's file.
Intelligent routing picks the depth: you describe the question, and the server says which path answers it and why. Analytics is repeatable: same data, same numbers. Every report names its method and the code that ran it, and runs again on new data.
It is for business and statistical questions about data, not a general-purpose assistant.
Website: mcpanalytics.ai · Free tools you can try in the browser: mcpanalytics.ai/free
Connect
**Endpoint:** https://api.mcpanalytics.ai/mcp/api-key (Streamable HTTP, JSON-RPC)
**Authentication:** an API key in the X-API-Key header. Create an account at mcpanalytics.ai and copy your key from your account settings.
**Claude Code:**
**Browse before you sign up.** Without a key the server answers in discovery mode: you can connect and list the tools, but not run anything.
Start
Ask your AI assistant a question about your data, for example:
- "Upload sales.csv. What changed in revenue from May to June, and which channel drove it?"
- "Which customers are most likely to churn?"
- "Forecast next quarter's sales from this file."
The first call is the resolver: it reads your question and your data, executes nothing and charges nothing, and names the path that answers it (an answer, a library analysis, or a custom build) with the reason. Then it runs that path.
What you get
- A report with charts, tables and a written interpretation, with its method named and the code that ran it.
- Re-runs on new data: run the same analysis on next month's file.
- Source
- awesome · https://github.com/embeddedlayers/mcp-analytics
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