Polar Analytics MCP Server
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Polar Analytics
Every source reconciled behind a single endpoint, using your own metric definitions: get_context, generate_report, list_dimensions, get_dashboard_details.
This server is the one that answers questions no single platform can. Every other connector in this directory sees one source: Shopify knows orders, Klaviyo knows flows, Google Ads knows spend. None of them knows what a customer is worth or what a channel actually contributed. Polar sits on a dedicated warehouse fed by 45+ connectors, reconciles it all into one model, and exposes it through a semantic layer where your definitions of CAC, LTV and contribution margin are already written down. The agent queries concepts, not columns, and every number it returns can be clicked back to its source.
It does not make the other connectors useless, it makes them comparable.
Key Features
- One endpoint over 45+ sources: deduplicated, timezone-aligned, currency-converted.
- Governed semantic layer: blended CAC, LTV, contribution margin and net revenue defined once, used everywhere.
- Totals returned alongside the rows, so the model never sums anything itself.
- Your dashboards and saved views are readable by the agent, and deep-link back into Polar.
- Read-only: nothing is written back to your store, your ad accounts or your ESP.
- Pre-built prompts for Executive Summary, Inventory Optimization, Profitability Deep-dive, CRO, Email Revenue, Creative Performance and Media Buying Health Check.
Use Cases
- The Monday executive summary, pulled live: net sales against plan, blended ROAS by channel, top movers, anomalies.
- "Why did this drop?" as a conversation rather than a dashboard, down to a root cause with a number attached.
- Cohort and retention questions that used to mean an analyst ticket and a SQL query.
- Scheduled agents that read the last seven days and write prioritised actions into Slack or Notion.
Tools
11
get_contextTells the agent your company, currency, timezone, connected sources, available metrics and dimensions.generate_reportReturns trusted numbers with explicit metrics, dimensions, date range, filters and ordering, totals included.get_metricsLists the metrics defined in your semantic layer.list_dimensionsSurfaces every attribution model, custom dimension and saved view defined in Polar.get_dimension_valuesReturns the values available for a dimension.get_custom_dimension_detailsReads the definition of a custom dimension.get_view_detailsReads the details of a saved view.list_dashboardsLists the dashboards and reports your team has already built.get_dashboard_detailsReads one dashboard and summarises it.generate_app_report_linkReturns a link to the matching report inside Polar.rate_reportRecords feedback on a report.
Connect it
What you need before the first question, and where it goes.
Claude Code / Cursor / VS Code
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Already on Polar? One click from Connectors in Claude, no config file. The token pair is generated at app.polaranalytics.com/mcp. { "mcpServers": { "polar": { "url": "https://api.polaranalytics.com/mcp", "headers": { "Authorization": "Bearer TENANT_ID|SERVICE_TOKEN" } } } }
An MCP server is only as good as the data underneath it.
Polar connects this source to 120+ others in one semantic layer, so your agent answers on the same numbers your team reports on.
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