mcpbeat

Analytics MCP Server

ai.mcpanalytics/analytics
answering

Analytics is answering right now. Last checked 11 min ago. It exposes 15 tools. Last commit 2 Aug 2026.

The statistical analyst in your AI chat — validated, citable, re-runnable analysis of your data.

Uptime history 39 hours of history
39 hours agonow
100.0%
Uptime 24h
182 of 182 checks
15
Tools
read from the server
533 ms
Response time
average over 24h
7
Stars
last commit 2 Aug 2026

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 11 min ago.

run in your terminal
claude mcp add analytics --transport http https://api.mcpanalytics.ai/auth0
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "analytics": {
      "url": "https://api.mcpanalytics.ai/auth0"
    }
  }
}
~/.codex/config.toml
[mcp_servers.analytics]
url = "https://api.mcpanalytics.ai/auth0"
.cursor/mcp.json
{
  "mcpServers": {
    "analytics": {
      "url": "https://api.mcpanalytics.ai/auth0"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "analytics": {
      "url": "https://api.mcpanalytics.ai/auth0"
    }
  }
}

This endpoint answered with an authorization challenge — the server is running, but you need an API key or OAuth to use it.

Available tools 15

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

analysis
create_analysis
Commission a NEW analysis built for your question. tier is REQUIRED — the user picks. Easiest: fuzzy_request (plain language) + dataset_ref + tier. Snapshot = instant automated report (~2-10 min). JSON = a fast computed answer, numbers + method, re-runnable tool you own (~5 min). Brief = the computed answer on a one-page report — chart, numbers, method (~7 min). Deck = commissioned deep analysis, a durable re-runnable module you own (30-45 min). Failed builds are never billed.
run_analysis
Run an analysis on your data. Returns a shareable interactive report URL — validated statistics you can cite, re-run, and share.
datasets
datasets_list
List and search your uploaded datasets — fuzzy matching on name, description, and tags. Returns each dataset's uuid:// reference for use in create_analysis and run_analysis.
datasets_upload
Get your data in. Pass `data` as an array of row objects to create the dataset immediately and get a dataset_ref ready for create_analysis; omit it to get an upload link for a file only the user can reach.
reports
reports_list
Your report library — every analysis delivered, with status and links. Pass semantic_query to search report content in plain language.
reports_view
Get a shareable browser link for a report — viewable without authentication.
about
about
Platform documentation and info — how it works, tiers, usage.
account
account_link
Direct link to the right account page for anything not doable in chat — billing, browser upload, report management. Hand the user the link and guide them.
agent
agent_advisor
AI help desk — which analysis fits your question, interpreting results, fixing errors. Multi-turn.
ask
ask_library
Ask a question across all your delivered analyses — synthesized answer with citations back to specific reports.
build
build_status
Check a commissioned build in-chat: stage progress, queue position, rejection reason if the data didn't match the objective, honest ETA, report link when delivered.
discover
discover_tools
Browse the analyses you can run — the ones you commissioned plus the platform Standard Library (prebuilt tools; each result tagged source:'own' or 'standard_library'). Plain-language match; no query lists everything, your own first. Nothing fits? Commission it with create_analysis.
modify
modify_analysis
Modify an EXISTING analysis into a new version — reword the question, swap the method, or add a variable. Pass tool_name + changes (plain language). Rebuilds on the analysis's own dataset by default; the original stays put. Returns pipeline tracking — follow with build_status.
report
report_cards
Browse a delivered report's individual cards (charts, tables, insights) inline in chat.
tools
tools_schema
Get an analysis's parameter schema — ALWAYS call before run_analysis.

Endpoints

URLTransportStateLatencyChecked
https://api.mcpanalytics.ai/auth0 streamable-http needs key 557 ms 12 min ago
https://api.mcpanalytics.ai/mcp/api-key streamable-http answering 571 ms 11 min ago

Analytics — questions

Answers built from our own checks of this server.

What can Analytics do?
It exposes 15 tools, read directly from the server on our last check. Among them: about, account_link, agent_advisor, ask_library, build_status, create_analysis and 9 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is Analytics mostly used for?
Its tools cluster around datasets, analysis and reports. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is Analytics working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 182 of 182 checks got a reply (100.0%), average response time 533 ms. The bar chart above shows every period we have measured.
How do I connect Analytics?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address. You will need your own key or an OAuth login: it refuses anonymous clients.
Does Analytics need an API key?
Yes. Every time we knock, Analytics answers with an authorization challenge instead of its tool list — that is how we know it is running and gated rather than broken. Bring your own credentials and it will talk.
How fast is Analytics?
It answers our handshake in 533 ms on average, which is faster than 20% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.
Is Analytics open source?
Yes — it is published under the MIT licence, written in JavaScript, 7 stars on GitHub and 4 open issues. The source link is on this page, so you can read exactly what it does with your data before you connect it.