Integration
Connect Trail to Google Cloud Scheduler
When Task Completed fires in Trail, your agent runs Create HTTP Job in Google Cloud Scheduler. 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 Trail and Google Cloud Scheduler 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)Grok
Open grok.com/connectors, choose New Connector, then Custom, and paste the address. Grok signs you in in your browser.
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 Trail can start in Google Cloud Scheduler
When Task Completed in Trail
then Create HTTP Job in Google Cloud Scheduler
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 Trail and Google Cloud Scheduler
Triggers and actions 1 trigger · 19 actions
- Task Completed
Triggers when a task from the chosen Trail task templates is completed at any site.
- Create Task
Creates a task at a Trail site from an automated task template, with an optional due window and description.
- Find Tasks
Returns the Trail tasks due in a date range for the chosen task templates, with their status and completion details.
- Get Scores
Returns Trail task-completion scores for each day, week or month in a date range, optionally filtered by site, area, tag or template.
- Get Task
Returns one Trail task by its ID, including its checklist, comments and tags.
- Get Task Checklists
Returns the checklist items and their completion status for the given Trail tasks.
- Get Task Comments
Returns the comments left on the given Trail tasks.
- Get Task Record Logs
Returns the record logs (recorded readings and values) for the given Trail tasks.
- List Areas
Returns all areas (groups of sites) in your Trail account.
- List Sites
Returns all sites (locations) in your Trail account.
- List Tags
Returns all tags in your Trail account.
- List Task Templates
Returns all task templates in your Trail account.
- Create HTTP Job
Creates a Cloud Scheduler job that calls an HTTP URL on a cron schedule.
- Delete Job
Permanently deletes a Cloud Scheduler job.
- Get Job
Returns a Cloud Scheduler job's schedule, target and current state.
- List Jobs
Returns the Cloud Scheduler jobs in a project location.
- Pause Job
Pauses a Cloud Scheduler job so it stops running on its schedule until resumed.
- Resume Job
Resumes a paused Cloud Scheduler job so it runs on its schedule again.
- Run Job Now
Runs a Cloud Scheduler job immediately. The job must be enabled; a paused job has to be resumed first.
- Update Job
Changes a Cloud Scheduler HTTP job's schedule, time zone, URL, method or description. Fields left blank are not changed.
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
Trail and Google Cloud Scheduler, answered
What can start an automation from Trail?
Any of Trail's 1 trigger in the catalog, including Task Completed. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Google Cloud Scheduler when something happens in Trail?
Any of Google Cloud Scheduler's 8 actions, including Create HTTP Job, Update Job, Get Job and List Jobs. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Google Cloud Scheduler to Trail?
Google Cloud Scheduler has no triggers in the catalog today, so automations start in Trail. If you need the other direction, ask: your agent reads Google Cloud Scheduler's API documentation and adds it.
Do I have to build a connector for Trail or Google Cloud Scheduler?
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 Trail and Google Cloud Scheduler 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.