Integration
Connect Databox to ScraperAPI
When New Dataset fires in Databox, your agent runs Add DataPipeline project in ScraperAPI. 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 Databox and ScraperAPI 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 Databox can start in ScraperAPI
When New Dataset in Databox
then Add DataPipeline project in ScraperAPI
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 Databox and ScraperAPI
Triggers and actions 1 trigger · 21 actions
- New Dataset
Triggers when a new dataset is created in your Databox organization.
- Create Dataset
Creates a dataset with the given columns inside a Databox data source.
- Delete Dataset
Permanently deletes a Databox dataset and all its data.
- Delete Data Source
Permanently deletes a Databox data source and every dataset in it.
- Get Dataset
Returns the details of one Databox dataset.
- Get Dataset Ingestion
Returns the details of one data ingestion into a Databox dataset, including its status, duration, record counts and any errors.
- Get Metric Data
Returns a Databox metric's values for a date range at the chosen granularity.
- Ingest Data into Dataset
Adds a batch of up to 100 records to a Databox dataset.
- List Dashboards
Lists the dashboards in your Databox organization.
- List Datasets
Lists Databox datasets, optionally filtered by data source or name.
- List Data Sources
Lists the data sources in your Databox organization.
- Purge Dataset
Removes all rows from a Databox dataset while keeping the dataset itself.
- Add async scrape job
Submit an asynchronous scraping job.
- Add async scrape jobs in batch
Submit many URLs as async jobs in one call.
- Add DataPipeline project
Create a DataPipeline project with input list, schedule and settings.
- Cancel Crawler Job
Cancel an active crawler job by its job ID.
- Create Crawler Job
Start a one-off crawler job that follows links from a starting URL and streams page results to a webhook.
- Delete DataPipeline project
Archive a DataPipeline project.
- Extract Data From URL
Extract data from a URL — HTML, Markdown, plain text, or parsed JSON. Handles proxies, browser rendering, and CAPTCHAs.
- Get account usage
Return plan limits, request counts, failed request count and concurrent requests.
- Get Structured Data
Retrieve parsed data from supported source categories. Choose a category and operation to get clean JSON.
- Update DataPipeline project
Edit a DataPipeline project's settings/schedule/input.
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
Databox and ScraperAPI, answered
What can start an automation from Databox?
Any of Databox's 1 trigger in the catalog, including New Dataset. Describe the moment in plain language and your agent picks the right one.
What can your agent do in ScraperAPI when something happens in Databox?
Any of ScraperAPI's 10 actions, including Create Crawler Job, Update DataPipeline project, Add async scrape job and Add async scrape jobs in batch. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from ScraperAPI to Databox?
ScraperAPI has no triggers in the catalog today, so automations start in Databox. If you need the other direction, ask: your agent reads ScraperAPI's API documentation and adds it.
Do I have to build a connector for Databox or ScraperAPI?
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 Databox and ScraperAPI 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.