Integration
Connect Databox to Azure Ai Vision
When New Dataset fires in Databox, your agent runs Analyze Image in Azure Ai Vision. 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 Azure Ai Vision 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 Databox can start in Azure Ai Vision
When New Dataset in Databox
then Analyze Image in Azure Ai Vision
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 Azure Ai Vision
Triggers and actions 1 trigger · 17 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.
- List Metrics
Lists the metrics in your Databox organization.
- Purge Dataset
Removes all rows from a Databox dataset while keeping the dataset itself.
- Analyze Image
Analyzes an image and returns the visual features you ask for: caption, tags, categories, objects, brands, dominant colors, image type and adult-content scores.
- Describe Image
Generates human-readable captions for an image, ranked by confidence, plus descriptive tags.
- Detect Objects
Finds objects in an image and returns each one's name, confidence and bounding box.
- Extract Text from Image (OCR)
Reads printed and handwritten text in an image and returns the full text plus each line with its position.
- Tag Image
Returns content tags for an image (objects, living beings, scenery and actions), each with a confidence score.
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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More into Azure Ai Vision
Questions
Databox and Azure Ai Vision, 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 Azure Ai Vision when something happens in Databox?
Any of Azure Ai Vision's 5 actions, including Analyze Image, Describe Image, Detect Objects and Extract Text from Image (OCR). Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Azure Ai Vision to Databox?
Azure Ai Vision has no triggers in the catalog today, so automations start in Databox. If you need the other direction, ask: your agent reads Azure Ai Vision's API documentation and adds it.
Do I have to build a connector for Databox or Azure Ai Vision?
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 Azure Ai Vision 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.