Integration
Connect Azurevirtualmachines to Qdrant Vector Store
When New Virtual Machine fires in Azurevirtualmachines, your agent runs Add collection in Qdrant Vector Store. 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 Azurevirtualmachines and Qdrant Vector Store 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 Azurevirtualmachines can start in Qdrant Vector Store
When New Virtual Machine in Azurevirtualmachines
then Add collection in Qdrant Vector Store
When New Virtual Machine in Azurevirtualmachines
then Add payload index in Qdrant Vector Store
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 Azurevirtualmachines and Qdrant Vector Store
Triggers and actions 1 trigger · 26 actions
Trigger
New Virtual MachineTriggers when a new virtual machine appears in an Azure subscription.
Action
Deallocate Virtual MachineShuts down an Azure virtual machine and releases its compute resources, so compute charges stop until it is started again.
Action
Get Virtual MachineReturns a virtual machine's details and its current power state (running, stopped or deallocated).
Action
List Available VM SizesReturns the virtual machine sizes offered in an Azure region, with CPU and memory, and whether each is available to the subscription.
Action
List LocationsReturns the Azure regions available to a subscription.
Action
List Resource GroupsReturns the resource groups in an Azure subscription.
Action
List SubscriptionsReturns the Azure subscriptions the connected app registration can access.
Action
List Virtual MachinesReturns every virtual machine in an Azure subscription, with its size, region and resource group.
Action
List Virtual Machines in Resource GroupReturns the virtual machines in one Azure resource group, with their size and region.
Action
Power Off Virtual MachinePowers off an Azure virtual machine. The machine stops running but stays allocated, so compute charges continue; use Deallocate Virtual Machine to stop them.
Action
Restart Virtual MachineRestarts a running Azure virtual machine. Azure accepts the request and reboots the machine in the background.
Action
Start Virtual MachineStarts a stopped or deallocated Azure virtual machine. Azure accepts the request and powers the machine on in the background.
Action
Add collectionCreates a new Qdrant collection with the vector size, distance metric and storage settings you choose.
Action
Add payload indexCreates a payload index on a field of a Qdrant collection so filters and searches on that field run faster.
Action
Add pointsAdds points (vectors with optional payloads) to a Qdrant collection, overwriting any existing points that have the same ids.
Action
Add snapshotCreates a new snapshot of a Qdrant collection and returns the snapshot's name, size, checksum and creation time.
Action
Count pointsReturns how many points in a Qdrant collection match an optional filter, or the total number of points when no filter is given.
Action
Delete collectionDeletes a collection and all of the points and data stored in it.
Action
Delete pointsDeletes points from a Qdrant collection, either by a list of point ids or by every point matching a filter.
Action
Find points by vectorReturns the points in a collection whose vectors are nearest to the vector you supply, ranked by similarity score, with their payloads.
Action
Get collectionReturns the details of a collection: its status, point and segment counts, vector and index configuration, and payload schema.
Action
Get pointReturns a single point from a Qdrant collection by its id, including its payload and vector.
Action
List collectionsReturns the names of every collection in your Qdrant instance.
Action
List pointsReturns the points stored in a Qdrant collection, optionally narrowed by a filter and ordered by a payload field, fetching every page.
Action
List snapshotsReturns every snapshot taken of a collection, with each snapshot's name, size, checksum and creation time.
Action
Update collectionUpdates the settings of an existing Qdrant collection, such as its vector, index, optimizer, quantization, strict-mode or metadata parameters.
Action
Update point payloadSets payload values on the chosen points in a Qdrant collection, merging them into each point's existing payload. Pick the points by id or by a filter.
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
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Questions
Azurevirtualmachines and Qdrant Vector Store, answered
What can start an automation from Azurevirtualmachines?
Any of Azurevirtualmachines's 1 trigger in the catalog, including New Virtual Machine. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Qdrant Vector Store when something happens in Azurevirtualmachines?
Any of Qdrant Vector Store's 15 actions, including Update collection, Update point payload, Add collection and Add payload index. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Qdrant Vector Store to Azurevirtualmachines?
Qdrant Vector Store has no triggers in the catalog today, so automations start in Azurevirtualmachines. If you need the other direction, ask: your agent reads Qdrant Vector Store's API documentation and adds it.
Do I have to build a connector for Azurevirtualmachines or Qdrant Vector Store?
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 Azurevirtualmachines and Qdrant Vector Store 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.