Make

Connect Make to the Clics remote MCP server for visual analytics automations.

Connect Clics to Make

Use Make’s MCP client capabilities to bring Clics tools into visual automation scenarios. This is an MCP connection, not a native Clics Make app.

1. Use the Clics remote MCP URL

https://api.clics.dev/v1/mcp

2. Add Clics as an MCP server

In a Make scenario or AI Agent, add the MCP Client capability and create a remote server connection. Enter the Clics URL, select Streamable HTTP, and complete OAuth authorization. If your Make MCP Client does not support OAuth discovery, use the Clics REST API instead.

3. Map the result

Choose a Clics tool, provide its required input, and map the returned structured content into the next module. Run the scenario once with test data before scheduling it.

Good first workflows include weekly analytics summaries, goal alerts, funnel checks, and post-deploy traffic reports.

Recommended scenario structure

Build scenarios in small, observable stages:

1. Start with a scheduler, webhook, or manual trigger.
2. Call one Clics tool through the MCP Client.
3. Transform the structured result with Make functions.
4. Add filters for thresholds or empty results.
5. Route the final values to the destination modules.

Keep the first version read-only. Add create or update tools only after the reporting path is stable.

Example scenarios

Multi-channel performance report

Call query_stats, aggregate visitors and conversions by source, and route formatted summaries to different team channels or client workspaces.

Post-deploy analytics check

Trigger the scenario from a deployment webhook, wait for an observation window, then compare current traffic and goal conversions with the previous period.

Funnel health monitor

Retrieve a funnel, calculate its current completion rate, and use a Router to send healthy and degraded results down separate paths.

Session review pipeline

List recent sessions, iterate over selected session IDs, retrieve their events, and store concise journey summaries in your review system.

Mapping Clics output

Clics MCP tools return structured content alongside a text representation. Prefer structured fields when mapping modules. Add a JSON parsing step only when Make exposes the result as a text string.

When processing lists:

• Use an Iterator for individual projects, funnels, or sessions
• Use an Aggregator before sending one combined report
• Filter empty arrays before downstream modules
• Store a baseline in a Data Store when comparing runs over time

Troubleshooting