Overview
Polar MCP lets you connect your Polar Analytics workspace to Make so your AI agents and automations can work with live ecommerce and marketing data instead of static exports. This is useful when you want to automate recurring reporting, trigger alerts when performance changes, or generate summaries that combine Polar data with tools like Gmail, Slack, or Google Sheets. Polar’s MCP is a secure, read-only bridge to your Polar workspace, and the current Make flow uses an AI Agent connected to an MCP server rather than a legacy raw HTTP-only setup.
In this guide, you will learn how to:
connect Polar MCP to Make
authenticate the connection correctly
build a simple scenario with Run an agent
test, troubleshoot, and safely scale the setup
Section 1: Before you start
Before setting up Polar MCP in Make, make sure you have:
an active Polar Analytics account with access to the correct workspace
a Make account with access to AI Agents
at least one connected data source in Polar, such as Shopify, Meta Ads, or Google Ads
permission to generate or access the Polar authentication credential used for MCP in your workspace
What this setup does
This setup gives a Make AI Agent access to Polar tools through MCP. Once connected, the agent can use Polar data inside a scenario and pass the result into downstream steps such as Markdown to HTML, Gmail, Slack, or Sheets. The intended flow: create an agent, add the Polar MCP server, then use Run an agent in the scenario.
Polar MCP endpoint
Use this MCP server URL in Make:
Section 2: Authentication details
Authentication method: Polar workspace token / MCP key from Polar
Where to get it: Polar MCP page in the app (app.polaranalytics.com/mcp) or your organization developer/token area, depending on your workspace setup
What to enter in Make: the credential requested when adding the MCP server connection to your AI Agent
Authentication note: Polar MCP credentials may appear in Polar either as an MCP key in the MCP setup page or as an organization access token in your developer settings, depending on your account configuration. When connecting Polar MCP to Make, use the credential provided in Polar for MCP access and keep it stored securely in Make. If you are following an older HTTP-based setup, you may see Basic Authentication instructions in legacy documentation, but the preferred flow for Make AI Agents is to connect Polar as an MCP server directly.
Security best practices
Do not paste Polar credentials into prompts or shared docs.
Store the credential only inside the Make connection.
Use a shared admin-owned Polar setup when the automation should outlive an individual employee.
Recheck permissions if the workspace, token, or connected data sources change.
Section 3: Step-by-step setup in Make
Step 1: Create an AI Agent in Make
In Make, go to AI Agents and create a new agent. Add a clear system prompt that tells the agent how to use Polar data. Make’s AI Agent configuration docs explain that the system prompt defines the agent’s purpose, behavior, and constraints across workflows.
Step 2: Add Polar as an MCP server
Inside the agent configuration, go to the MCP section and click Add. This is where you connect an agent to MCP servers and then enable the tools you want the agent to access.
Choose New MCP server and enter:
Server URL:
https://api.polaranalytics.com/mcpAuthentication credential: your Polar MCP key or Polar access token from Polar
Server name: Polar MCP
After the connection is created, enable the Polar tools and save the agent. Enabled MCP tools become available to the agent and can be reviewed later in the Run an agent module.
Step 3: Build your scenario
Create a new scenario in Make and add the Run an agent module. Select the agent you just configured.
From here, add whatever downstream steps you want. Common examples:
Markdown to HTML to format the output
Gmail to email a report
Slack to post alerts
Google Sheets to log results over time
Step 4: Add your agent instruction in the scenario
In the Run an agent step, give Make a clear task, for example:
Summarize yesterday’s performance by channel using Polar. Include spend, revenue, ROAS, and the biggest change versus the prior day. Keep it under 200 words.
Step 5: Test the workflow
Run the scenario once and review:
whether the agent can call Polar tools successfully
whether the output contains current workspace data
whether downstream steps receive the expected format
Then turn on scheduling for the cadence you want, such as daily summaries every morning.
Section 4: Example workflow readers can copy
Daily performance email from Polar
A simple starter automation:
Run an agent
Prompt the agent to summarize yesterday’s revenue, spend, ROAS, and top changes.Markdown to HTML
Format the agent’s answer for email.Gmail
Send the summary to your team.Schedule
Run daily at a set time.
Example prompt
Using Polar data, generate a daily executive summary for yesterday. Include total revenue, ad spend, blended ROAS, top-performing channel, weakest channel, and one action item for the team.
Section 5: Troubleshooting
The MCP server will not connect
Check that:
the server URL is exactly
https://api.polaranalytics.com/mcpthe Polar credential is valid and copied completely
the credential belongs to the correct Polar workspace or organization context
The agent connects, but returns weak or empty answers
Check that:
your Polar workspace has active data sources connected
the correct workspace is selected in Polar
your system prompt tells the agent what business questions to answer
the requested date range or metric names are reasonable for the available data
Conclusion
Using Polar MCP in Make gives customers a practical way to turn Polar into an automation layer for reporting, alerts, and AI-driven analysis. The clearest setup path today is to create a Make AI Agent, add Polar as an MCP server using the Polar MCP endpoint, authenticate with the Polar credential provided in-app, then use Run an agent inside a scenario to generate outputs for Gmail, Slack, Sheets, and more.
Key takeaways:
Use the Polar MCP endpoint:
https://api.polaranalytics.com/mcpPrefer the AI Agent + MCP server workflow in Make
Authenticate with the Polar MCP credential or organization access token supplied by Polar
Use downstream modules to turn Polar outputs into real workflows and alerts