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MCP Analytics

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The statistical analyst in your AI chat — bring data and a question, own a citable, re-runnable analysis.
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★ 7 Stars Category · Other Popular Source revision f40a34d968de
53FMRS · D

MCP Analytics extends AI assistants with citable, reproducible, and methodologically validated statistical reports. Its tiered model from free Snapshots to deep Deck studies is careful to bill only on success. It offers multiple transport options, auth-free discovery, and a browsable tool catalog, making it easy to try. Main caveats: commercial nature, cloud processing (not for sensitive data), and it's a third-party service, not official.

Reliability
8/20
Security and permissions
12/20
Maintenance
8/20
Documentation
12/20
Setup experience
13/20
Read the FMRS scoring method →

MCP Analytics is a statistical analyst inside your AI chat. You provide data (CSV or live connectors) and a question; a team of specialist agents builds a custom analysis specific to your data, validates methodology, and delivers an interactive, citable report. The analysis is yours—it lives in your private library, reruns on fresh data at a fraction of the cost, and is queryable from Claude, Cursor, or any MCP client. Multiple depth tiers are available, from instant Snapshots to full Deck studies, with pre-built cornerstone modules covering t-tests, regression, clustering, time series, and more. The platform prioritizes rigorous statistical methods over decorative charts.

Tools

create_analysis
Commission a new analysis from a plain-language question at your chosen tier (snapshot, JSON, brief, or deck).
build_status
Track a build: stage progress, queue position, and report link.
run_analysis
Run an analysis you own (or one discovered via discover_tools) on fresh data.
modify_analysis
Turn an existing analysis into a new version — reword the question or change framing.
discover_tools
Browse what you can run: your commissioned analyses plus the prebuilt library.
tools_schema
Get an analysis's parameter schema — always call this before run_analysis.
datasets_upload
Secure data upload with encryption.
datasets_list
List and search your uploaded datasets.
connectors_list
List available data source connections (e.g., GA4, GSC).
connectors_query
Pull live data from a connected source.
reports_view
Get a shareable browser link for a report.
reports_list
Your report library — searchable in plain language.
report_cards
Browse a delivered report's individual cards (charts, tables, insights).
ask_library
Ask one question across all delivered analyses; get a synthesized answer with citations.
agent_advisor
AI help desk — which analysis fits your question and how to read results.
billing
Usage and credit management.
account_link
Get a link to account pages for anything not doable in chat.
about
Platform documentation and info on how it works, tiers, usage.

Setup

  1. Sign up at account.mcpanalytics.ai and copy your API key (starts with mcp_). You receive 500 welcome credits — no credit card required.
  2. Add the mcpServers configuration to your MCP client (Claude Desktop, Cursor, Windsurf, etc.).
  3. Alternatively, connect via Streamable HTTP using the token URL with your API key, or via OAuth2 for zero-config.
  4. Restart the client and start asking questions.
claude_desktop_config.json
{
  "mcpServers": {
    "mcpanalytics": {
      "command": "npx",
      "args": [
        "-y",
        "@mcp-analytics/mcp-analytics"
      ],
      "env": {
        "MCP_ANALYTICS_API_KEY": "mcp_your_key_here"
      }
    }
  }
}

Fit and risk

Best for

  • Business analysts and data science enthusiasts seeking rigorous statistical analysis through an AI chat interface.
  • Teams needing citable, reproducible analyses with methodology descriptions for papers, presentations, or compliance.
  • Users who want to own their analysis modules and rerun them on fresh data without paying again.
  • Adopters of Claude Desktop, Cursor, Windsurf, or other MCP clients who want to analyze data directly in their workflow.

Not for

  • Users needing a free or open-source solution (service is commercial, credit-based).
  • Users who just need simple SQL queries or file system operations (more specialized, free MCP servers exist).
  • Users requiring fully local processing to avoid cloud (data is sent to API for processing).
  • Users needing very large-scale data processing or non-statistical custom coding (platform focuses on statistical methods).

Required permissions

  • Tools can read uploaded CSVs or pull data from connected sources (GA4, GSC).
  • Running analyses involves calling remote cloud APIs; network access required.
  • Auth via OAuth2 (Auth0) or API key.
  • Billing tool can affect credit usage within this API (not external payments).
  • May create or update remote connector data if supported.

Risks and side effects

  • Data is processed in the cloud, so sensitive information could be exposed despite encryption and ephemeral processing.
  • Commercial service relies on credits; builds that fail are not billed, but continued use requires payment.
  • Non-official, third-party service may have rate limits or downtime.
  • Potential for errors in AI-generated analyses if used without scrutiny; platform claims verification, but users should review.

Troubleshooting

  1. Ensure your config file is valid JSON.
  2. Restart the MCP client completely.
  3. Verify your API key starts with mcp_.
  4. Check the client's developer console for errors.
  5. Run the npx command in a terminal manually to se errors (should output 'Connected to ...').
  6. Contact support at [email protected].

Use cases

Upload a CSV and ask a question (e.g., 'Does ad spend drive sales?') and get a statistical answer.
Segment your customers (clustering) or predict churn on your data.
Forecast next quarter's revenue from time series data.
Run hypothesis tests or regression on survey data.
Share citable, reproducible reports in papers, decks, or regulatory filings (APA/MLA/BibTeX).

Supported clients

Claude DesktopFull support
CursorFull support
WindsurfFull support
Claude CodeFull support