Integration
Connect Request Tracker (RT) to Qdrant Vector Store
When Ticket Created fires in Request Tracker (RT), 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 Request Tracker (RT) 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 Request Tracker (RT) can start in Qdrant Vector Store
When Ticket Created in Request Tracker (RT)
then Add collection in Qdrant Vector Store
When Ticket Status Changed in Request Tracker (RT)
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 Request Tracker (RT) and Qdrant Vector Store
Triggers and actions 3 triggers · 34 actions
Trigger
Ticket CorrespondenceTriggers when a ticket is replied to (that is, corresponded with).
Trigger
Ticket CreatedTriggers when a new Request Tracker ticket is created.
Trigger
Ticket Status ChangedTriggers when a Request Tracker ticket changes status. Can watch for any status change or only for changes to a specific status.
Action
Add assetCreate an asset.
Action
Add userCreate a user.
Action
Comment on a TicketAdd an internal comment to a ticket and send to any internal watchers.
Action
Create TicketCreate a new ticket in Request Tracker.
Action
Find AttachmentLocate an attachment by ID.
Action
Find TicketLocate a ticket by ID.
Action
Find TicketsIssue a query to find matching tickets.
Action
Find TransactionFind a transaction by ID
Action
Get assetRetrieves one asset by ID: name, description, status, catalog, owner, held by, contact, custom fields.
Action
Get queueGet a queue by id or name.
Action
Get userGet a user by id or name.
Action
List queuesList all queues visible to user.
Action
List ticket historyList transactions of a ticket.
Action
Reply to a TicketReply to the requestor and any internal or external watchers of a ticket.
Action
Update ticketGeneral ticket update (Owner, Priority, Queue, custom fields).
Action
Update Ticket Due DateUpdate the due date of a ticket.
Action
Update Ticket StatusUpdate the status of a ticket.
Action
Update Ticket SubjectUpdate the subject of a ticket.
Action
Update userUpdate a user.
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
What our customers say
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Questions
Request Tracker (RT) and Qdrant Vector Store, answered
What can start an automation from Request Tracker (RT)?
Any of Request Tracker (RT)'s 3 triggers in the catalog, including Ticket Created, Ticket Status Changed and Ticket Correspondence. 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 Request Tracker (RT)?
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 Request Tracker (RT)?
Qdrant Vector Store has no triggers in the catalog today, so automations start in Request Tracker (RT). 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 Request Tracker (RT) 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 Request Tracker (RT) 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.