Integration
Connect Google Cloud Logging to Google Gemini
When New Log Entry Matching Filter fires in Google Cloud Logging, your agent runs Count Tokens in Google Gemini. 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 Google Gemini to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiAny 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 Google Gemini
When New Log Entry Matching Filter in Google Cloud Logging
then Count Tokens in Google Gemini
When New Log Entry Matching Filter in Google Cloud Logging
then List Models in Google Gemini
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 Google Gemini
Triggers and actions 1 trigger ยท 5 actions
Trigger
New Log Entry Matching FilterTriggers when a new log entry matching a Cloud Logging filter is written to a project.
Action
List Log EntriesReturns log entries from a project that match a Cloud Logging filter, newest first.
Action
List LogsReturns the names of the logs in a project that have entries.
Action
Write Log EntryWrites a log entry to a Cloud Logging log in a project.
Action
Count TokensReturns how many tokens a piece of text uses for a chosen Gemini model.
Action
List ModelsReturns the Gemini models available to your API key, with their limits and capabilities.
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 Google Gemini, 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 Google Gemini when something happens in Google Cloud Logging?
Any of Google Gemini's 2 actions, including Count Tokens and List Models. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Google Gemini to Google Cloud Logging?
Google Gemini has no triggers in the catalog today, so automations start in Google Cloud Logging. If you need the other direction, ask: your agent reads Google Gemini's API documentation and adds it.
Do I have to build a connector for Google Cloud Logging or Google Gemini?
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.
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.