Integration
Connect Google Cloud Logging to Pipeless Recommendations
When New Log Entry Matching Filter fires in Google Cloud Logging, 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 Cloud Logging 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 Cloud Logging can start in Pipeless Recommendations
When New Log Entry Matching Filter in Google Cloud Logging
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 Cloud Logging and Pipeless Recommendations
Triggers and actions 1 trigger · 11 actions
- New Log Entry Matching Filter
Triggers when a new log entry matching a Cloud Logging filter is written to a project.
- List Log Entries
Returns log entries from a project that match a Cloud Logging filter, newest first.
- List Logs
Returns the names of the logs in a project that have entries.
- Write Log Entry
Writes a log entry to a Cloud Logging log in a project.
- 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 Cloud Logging and Pipeless Recommendations, answered
What can start an automation from Google Cloud Logging?
Any of Google Cloud Logging's 1 trigger in the catalog, including New Log Entry Matching Filter. 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 Cloud Logging?
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 Cloud Logging?
Pipeless Recommendations has no triggers in the catalog today, so automations start in Google Cloud Logging. 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 Cloud Logging 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 Cloud Logging 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.