Integration
Connect Azure DevOps and Databox
When Completed Build fires in Azure DevOps, your agent runs Create Dataset in Databox, or New Dataset in Databox to Add Link to Work Item in Azure DevOps. 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 Azure DevOps and Databox 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 Azure DevOps and Databox can do together
From Azure DevOps to Databox
When Completed Build in Azure DevOps
then Create Dataset in Databox
From Databox to Azure DevOps
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 Azure DevOps and Databox
Triggers and actions 6 triggers · 16 actions
- Code Push (Git)
Triggers when commits are pushed to a Git repository in an Azure DevOps project.
- Completed Build
Triggers when a build finishes in an Azure DevOps project, with its result (succeeded, failed, partially succeeded or canceled).
- New Work Item
Triggers when a work item is created in an Azure DevOps project.
- New Work Item Comment
Triggers when someone comments on a work item in an Azure DevOps project.
- Updated Work Item
Triggers when a work item is updated in an Azure DevOps project, with the work item's current values and the list of fields that changed.
- Add Link to Work Item
Adds a link to an Azure DevOps work item: a related, parent, child, predecessor, successor or duplicate link to another work item, or a hyperlink to a web page.
- Create Work Item
Creates a new work item (such as a Task, Bug, Issue or User Story) in an Azure DevOps project.
- Find Work Item
Finds work items in an Azure DevOps project that match a Work Item Query Language (WIQL) query, returning the matching work item IDs, or the matching links for a link query.
- Trigger Build
Queues a new run of an Azure DevOps build pipeline, optionally for a specific branch or commit and with pipeline variables or parameters.
- Update Work Item
Updates an existing Azure DevOps work item: changes its title, description, state, assignee, area, iteration, priority or tags, and can add a discussion comment. Fields left blank are not changed.
- 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.
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
Azure DevOps and Databox, answered
What can start an automation from Azure DevOps?
Any of Azure DevOps's 5 triggers in the catalog, including Completed Build, New Work Item, New Work Item Comment and Updated Work Item. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Databox when something happens in Azure DevOps?
Any of Databox's 11 actions, including Create Dataset, Get Dataset, Get Dataset Ingestion and Get Metric Data. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Databox to Azure DevOps?
Yes. When something happens in Databox, your agent can act in Azure DevOps too. This page covers both directions: Databox's triggers and Azure DevOps's actions are listed here as well.
Do I have to build a connector for Azure DevOps or Databox?
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 Azure DevOps and Databox 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.