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PopNx MCPMCP servers for people who use AI · explained in plain words

MCP Analytics

by embeddedlayersversion 1.0.8i★ –iRuns in the cloud
Registry nameai.mcpanalytics/analytics

Install

Overview

Description from the maker (original English)

A statistical analyst in your AI chat: bring data and a question, get a citable, re-runnable report.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs in the cloud
  • Transport: Streamable HTTP
  • Category: Marketing & social media
  • You need to fill in: X-API-Key

Install

Pick the AI app you use, then copy the settings.

Before you install

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Run this in your terminal

claude mcp add --transport http analytics https://api.mcpanalytics.ai/mcp/api-key --header 'X-API-Key: your-value'

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "analytics": {
      "url": "https://api.mcpanalytics.ai/mcp/api-key",
      "headers": {
        "X-API-Key": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "analytics": {
      "type": "http",
      "url": "https://api.mcpanalytics.ai/mcp/api-key",
      "headers": {
        "X-API-Key": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • X-API-Key secret required HTTP header
    Your MCP Analytics API key, from https://account.mcpanalytics.ai

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Tool names and descriptions exactly as the server reported them on Nov 8, 2026. The maker wrote them, not us; we show them as plain text.

  • 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.

  • about

    Platform documentation and info: how it works (Answer, Analytics, Custom Analytics), usage.

  • agent_advisor

    AI help desk: which analysis fits your question, interpreting results, fixing errors. Multi-turn.

  • 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 path_resolver; omit it to get an upload link for a file only the user can reach. Add replace_ref (uuid://ID:KEY) with data to REFRESH an existing dataset in

  • datasets_list

    List and search your uploaded datasets, with fuzzy matching on name, description, and tags. Returns each dataset's uuid:// reference (the `usage` field) for use as dataset_ref in path_resolver and path_tool_run. The id alone ('uuid://dsv2_...') also works for your own datasets an

  • 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 path_resolver.

  • tools_schema

    Get an analysis's parameter schema. ALWAYS call before path_tool_run.

  • review_estimate

    The estimate as you review it WITH the user: the question as understood, the estimated answer (sample, marked), every place and its question, the page link, a review checklist. Before path_bespoke.

  • adjust_estimate

    Apply the user's layout wishes to the estimate's page through the layout agent; a new named arrangement, nothing overwritten, no number changes.

  • find_precedent

    Before estimating: how did we answer this objective before, on this data or any data? Prior packages and library runs with their tools, mappings, bespoke module names, method and verdicts. Platform-wide, read-only.

  • check_tool_fit

    Before naming a library tool: does it fit THIS dataset for THIS question? Column mapping, missing required inputs, method-fit verdict, the places it delivers. Read-only.

  • package_status

    Read an analytics package back: status, every run under it, the report link once delivered.

  • my_objects

    List and search the objects you own across every question: the curated charts, tables and figures of each delivered package, grouped by objective.

  • 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.

  • ask_library

    Ask a question across all your delivered analyses: a synthesized answer with citations back to specific reports.

  • reports_list

    Your report library: every analysis delivered, with status and links. Pass semantic_query to search report content in plain language.

  • warehouse

    Query your org's data warehouse free: browse the catalog (tables with column roles + computed metrics), semantically find data, plain-language ask, or named templates. Requires warehouse enablement (business plans).

  • schedules

    Standing re-runs of analyses you own: action='create' (weekly/monthly against a re-runnable data reference, connector:// or an https:// link; report emailed after each run), 'list', or 'cancel'.

  • reports_view

    Get a shareable browser link for a report, viewable without authentication.

  • report_cards

    Browse a delivered report's individual cards (charts, tables, insights) inline in chat.

  • path_resolver

    Which path a question about data should take (reuse, rerun, answer, tool_run, estimate, bespoke, ask or none), with the reason, every path's score and time, and the ready input for the path it picks. Executes nothing and charges nothing.

  • path_reuse

    Hand back the report already delivered for this question on this data. Time: as path_resolver quotes.

  • path_rerun

    Run a delivered analysis again, on its own dataset or a new one: the same tools and mappings, no rebuild. package_id may also be the person's own report link (a /rpt/ link or its rpt_ token) or estimate id (est_); it reruns their newest delivered package for it. Time: as path_res

  • path_answer

    A read of the data (a total, an average, a count, the top group), computed on every row, in this response. When the question is not a read it says so and names the next step. Time: as path_resolver quotes. No key yet? Call it with objective and data (a small table, up to 200 rows

  • path_tool_run

    Run one or more tested library tools on this dataset, with charts and a written report. No custom build. Time: as path_resolver quotes.

  • path_estimate

    A rough answer over a sample and the layout of the full report, for the person to confirm before anything is ordered. Time: as path_resolver quotes.

  • path_bespoke

    Order a custom analysis built for this data from a confirmed estimate, optionally with library tools alongside. Needs the person's yes and an idempotency key; a retry returns the first order. Time: as path_resolver quotes.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified against the domain mcpanalytics.ai (the registry checks domain ownership)

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • ✓ Pass

    Endpoint responds

    Responded in 302 ms (HTTP 200)

  • – Not applicable

    Sign-in with OAuth

    No sign-in needed

  • ✓ Pass

    No hidden instructions in tool descriptions

    Read 27 tool descriptions and found no hidden instructions to the AI

Compared with others in Marketing & social mediai

  • More stars than 0% of the other 3577 servers in this category
  • Published to the registry more recently than 56% of the other 3577 servers in this category
  • Basic checks equal to or better than 100% of the other 3577 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MCP Analytics safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: X-API-Key

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.8) reached the registry 24 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

MCP Analytics

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.

{

"mcpServers": { "mcpanalytics": { "url": "https://api.mcpanalytics.ai/mcp/api-key", "headers": { "X-API-Key": "mcp_your_key_here" } } } }

Claude Code:

claude mcp add --transport http mcpanalytics https://api.mcpanalytics.ai/mcp/api-key --header "X-API-Key: mcp_your_key_here"

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.

curl -X POST https://api.mcpanalytics.ai/mcp/api-key \

-H 'Content-Type: application/json' \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

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.
  • A library of your reports you can search and ask questions across.

Data and privacy

Your uploaded data is used only to answer your questions. See the privacy policy for what we keep and for how long. Security issues: see SECURITY.md.

Support

License

See LICENSE.

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