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MCP v1.0.6 streamable-http

MCP Analytics

ai.mcpanalytics/analytics

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

Website ↗

Watch this dependency

Get before/after evidence when observed tools, schemas, authentication access, availability or the endpoint changes.

Inspect evidence and set up a watch Share public evidence report
Uptime
—
no probe counted in the 30d window
Response
557ms
earlier probe · not in the 30d uptime
Tools
15
callable
Resources
0
readable
Prompts
0
available
Primary URL
https://api.mcpanalytics.ai/mcp/api-key
Score: 45/100
The server exists but requires sign-in before we can list its tools.
why this score
partial Answers the MCP handshake 35/50
The endpoint answered HTTP 401 to an anonymous server/discover, so it exists, but we could not list its tools without credentials.
How to earn +15 points
Let anonymous clients discover what the server offers
Answer server/discover and tools/list without credentials and require auth only on tools/call. If the whole server must stay private, return a WWW-Authenticate header with resource_metadata pointing at /.well-known/oauth-protected-resource (RFC 9728) so MCP clients can sign in on their own; 2026-07-28 clients identify themselves with a Client ID Metadata Document rather than dynamic registration.
Docs →
n/a Lists tools, resources or prompts 0/30
Not scored: a catalogue only counts once the handshake succeeds.
n/a 3 or more catalogue items 0/10
Not scored: a catalogue only counts once the handshake succeeds.
pass Describes itself 10/10
100 characters; more than 30 earns these points.

Tools · 15

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, tiers, usage.

agent_advisor

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

datasets_upload

Get a secure upload token for your data file (CSV, Excel, JSON...). Returns the dataset UUID + key used everywhere else.

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.

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 l…

tools_schema

Get an analysis's parameter schema — ALWAYS call before run_analysis.

run_analysis

Run an analysis on your data. Returns a shareable interactive report URL — validated statistics you can cite, re-run, and share.

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). JSO…

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; …

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 — 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.

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.

How to use

Add to your Claude Desktop / Cursor / Cline MCP config:

{
  "mcpServers": {
    "mcp_analytics": {
      "url": "https://api.mcpanalytics.ai/mcp/api-key",
      "transport": "streamable-http"
    }
  }
}

Source: github.com/embeddedlayers/mcp-analytics