Integration
Connect Google Analytics to Pipeless Recommendations
When New Daily Report Row fires in Google Analytics, your agent runs Create Event in Pipeless Recommendations. Describe the whole flow and it is built, tested on every scenario and kept running.
What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.
Build solutions, not workarounds.
What do you want Google Analytics and Pipeless Recommendations to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiOne connection does both: ask your client to act in an app once, or have it build an automation that keeps running. Any client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser.
Set it up in your client
Claude Code
Run this in the directory you want to work in.
claude mcp add --transport http -s project apiant-ai https://mcp.apiant.aiStart Claude Code there, approve the server, and sign in in the browser page it opens.
Claude Code guide (opens in a new tab)Claude, web and desktop
Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first.
Setup guide (opens in a new tab)Cursor
Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser.
Setup guide (opens in a new tab)Zed
Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.
Setup guide (opens in a new tab)Codex and the ChatGPT desktop app
Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in.
Setup guide (opens in a new tab)Any other MCP client
Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection.
Setup guide (opens in a new tab)Example flows
What Google Analytics can start in Pipeless Recommendations
When New Daily Report Row in Google Analytics
then Create Event in Pipeless Recommendations
Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships.
Everything your agent can do with Google Analytics and Pipeless Recommendations
Triggers and actions 1 trigger · 15 actions
- New Daily Report Row
Triggers once for each report row of the previous full day (in the property's time zone), with the chosen dimensions and metrics as fields. Checks for yesterday's rows on every poll and delivers each row once.
- Get Metadata
Returns the dimensions and metrics available for reporting on a GA4 property, including custom ones.
- Get Property
Returns the details of one GA4 property, such as its name, time zone and currency.
- List Accounts
Returns the Google Analytics accounts the connected user can access.
- List Audiences
Returns the audiences defined on a GA4 property.
- List Properties
Returns the GA4 properties under an account.
- Run Realtime Report
Runs a GA4 realtime report covering the last 30 minutes of activity on a property.
- Run Report
Runs a GA4 report for the chosen dimensions, metrics and date range and returns one row per dimension combination.
- Create Event
Creates a single event linking a start object to an end object through a relationship (for example, a user who liked a post) in your Pipeless app.
- Create Events (With Line Item Support)
Creates up to 10 events in one call, such as several line items a user purchased.
- Delete event
Deletes the event(s) matching a start object, relationship type and end object.
- Delete object
Deletes an object and all the relationships and events connected to it.
- Get Activity on Object
Returns the activity that has taken place on an object, such as who followed or liked it.
- Get object
Returns basic info (type, created and modified dates) for a single Pipeless object.
- List recent events
Returns the most recent events (user–relationship–object interactions) that have been sent to your Pipeless app.
- Update object
Updates an existing Pipeless object's id or its created/modified timestamps.
No trigger or action matches that. Ask your agent to add it: it reads the API documentation and builds what you describe.
Each app on its own
Reviews
What our customers say
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Questions
Google Analytics and Pipeless Recommendations, answered
What can start an automation from Google Analytics?
Any of Google Analytics's 1 trigger in the catalog, including New Daily Report Row. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Pipeless Recommendations when something happens in Google Analytics?
Any of Pipeless Recommendations's 8 actions, including Create Event, Create Events (With Line Item Support), Update object and Get Activity on Object. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Pipeless Recommendations to Google Analytics?
Pipeless Recommendations has no triggers in the catalog today, so automations start in Google Analytics. If you need the other direction, ask: your agent reads Pipeless Recommendations's API documentation and adds it.
Do I have to build a connector for Google Analytics or Pipeless Recommendations?
No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running.
Can my AI client use Google Analytics and Pipeless Recommendations without building an automation?
Yes. With your AI client connected to APIANT, ask it to do something in either app once and it runs that action on the spot. Ask for an automation and your agent builds it, tests every scenario and keeps it running. One connection covers both.
What happens when something fails?
Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships.
Is there a free plan?
Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.