Integration
Connect Databox to Opportify
When New Dataset fires in Databox, your agent runs Create Email Batch Export in Opportify. 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 Opportify 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 Opportify
When New Dataset in Databox
then Create Email Batch Export in Opportify
When New Dataset in Databox
then Analyze Email in Opportify
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 Opportify
Triggers and actions 1 trigger · 17 actions
Trigger
New DatasetTriggers when a new dataset is created in your Databox organization.
Action
Create DatasetCreates a dataset with the given columns inside a Databox data source.
Action
Delete DatasetPermanently deletes a Databox dataset and all its data.
Action
Delete Data SourcePermanently deletes a Databox data source and every dataset in it.
Action
Get DatasetReturns the details of one Databox dataset.
Action
Get Dataset IngestionReturns the details of one data ingestion into a Databox dataset, including its status, duration, record counts and any errors.
Action
Get Metric DataReturns a Databox metric's values for a date range at the chosen granularity.
Action
Ingest Data into DatasetAdds a batch of up to 100 records to a Databox dataset.
Action
List DashboardsLists the dashboards in your Databox organization.
Action
List DatasetsLists Databox datasets, optionally filtered by data source or name.
Action
List Data SourcesLists the data sources in your Databox organization.
Action
Purge DatasetRemoves all rows from a Databox dataset while keeping the dataset itself.
Action
Analyze EmailPerform an AI-driven email analysis
Action
Analyze IP AddressPerform an AI-driven IP address analysis
Action
Batch Analyze EmailsSubmit a list of email addresses for asynchronous batch analysis. Returns a Job ID to track progress.
Action
Batch Analyze IPsSubmit a list of IP addresses (IPv4 or IPv6) for asynchronous batch analysis. Returns a Job ID to track progress.
Action
Create Email Batch ExportRequest a custom export (CSV or JSON) from a completed email batch job. Supports field filtering and column selection.
Action
Create IP Batch ExportRequest a custom export (CSV or JSON) from a completed IP batch job. Supports field filtering and column selection.
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 Opportify, 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 Opportify when something happens in Databox?
Any of Opportify's 6 actions, including Create Email Batch Export, Create IP Batch Export, Analyze Email and Analyze IP Address. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Opportify to Databox?
Opportify has no triggers in the catalog today, so automations start in Databox. If you need the other direction, ask: your agent reads Opportify's API documentation and adds it.
Do I have to build a connector for Databox or Opportify?
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 Opportify 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.