Integration
Connect OpenAI and Trengo
When something happens in OpenAI or Trengo, your agent does the next thing in the other. Describe it 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 OpenAI and Trengo to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiAny 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 OpenAI and Trengo can do together
From OpenAI to Trengo
When New batch in OpenAI
then Add internal note to ticket in Trengo
When New file in OpenAI
then Add ticket in Trengo
From Trengo to OpenAI
When New Internal Note in Trengo
then Create assistant in OpenAI
When New Outbound Message in Trengo
then Create message in OpenAI
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 OpenAI and Trengo
Triggers and actions 8 triggers · 84 actions
Trigger
New batchList your organization's batches.
Trigger
New fileReturns a list of files.
Trigger
New modelLists the currently available models.
Trigger
New vector storeReturns a list of vector stores.
Trigger
New videoList recently generated videos for the current project.
Action
Cancel batchCancels an in-progress batch.
Action
Cancel runCancels a run that is in_progress.
Action
Cancel vector store file batchCancel a vector store file batch.
Action
Content moderationClassifies text for hate, harassment, self-harm, sexual, and violence categories using the Moderations API.
Action
Count input tokensReturns input token counts of the request.
Action
Create assistantCreate an assistant with a model and instructions.
Action
Create chat completionSends a list of chat messages to a model via the Chat Completions API and returns the assistant's reply.
Action
Create completionCreates a completion for the provided prompt and parameters.
Action
Create embeddingGenerates a vector embedding for input text using an embeddings model (e.g. text-embedding-3-small).
Action
Create messageCreate a message.
Action
Create runCreate a run.
Action
Creates and executes a batch from an uploaded file of requestsCreates and executes a batch from an uploaded file of requests
Action
Create threadCreate a thread.
Action
Create thread and runCreate a thread and run it in one request.
Action
Create vector storeCreate a vector store.
Action
Create vector store fileCreate a vector store file by attaching a File to a vector store.
Action
Create vector store file batchCreate a vector store file batch.
Action
Create video edit jobCreate a new video generation job by editing a source or existing generated video.
Action
Create video extensionCreate an extension of a completed video.
Action
Create video generation jobCreate a new video generation job from a prompt and optional reference assets.
Action
Create video remixCreate a remix of a completed video using a refreshed prompt.
Action
Delete assistantDelete an assistant.
Action
Delete eval runDelete an eval run.
Action
Delete fileDelete a file and remove it from all vector stores.
Action
Delete messageDeletes a message.
Action
Delete threadDelete a thread.
Action
Delete vector storeDelete a vector store.
Action
Delete vector store fileDelete a vector store file (removes from store, file itself not deleted).
Action
Delete videoPermanently delete a completed or failed video and its stored assets.
Action
Download video contentDownload the generated video bytes or a derived preview asset.
Action
Edit imageCreates an edited or extended image given one or more source images and a prompt.
Action
Generate imageGenerates an image from a text prompt using gpt-image-1 / DALL-E and returns the image URL or base64 data.
Action
Generate speechConverts text into spoken audio using a TTS model and the selected voice. Returns audio bytes.
Action
Get assistantRetrieves an assistant.
Action
Get batchRetrieves a batch.
Action
Get fileReturns information about a specific file.
Action
Get file contentReturns the contents of the specified file.
Action
Get messageRetrieve a message.
Action
Get modelRetrieves a model instance.
Action
Get runRetrieves a run.
Action
Get run stepRetrieves a run step.
Action
Get threadRetrieves a thread.
Action
Get vector storeRetrieves a vector store.
Action
Get vector store fileRetrieves a vector store file.
Action
Get vector store file batchRetrieves a vector store file batch.
Action
Get vector store file contentRetrieve the parsed contents of a vector store file.
Action
Get videoFetch the latest metadata for a generated video.
Action
List conversation itemsList all items for a conversation with the given ID.
Action
List filesLists files that have been uploaded to your OpenAI account.
Action
List messagesReturns a list of messages for a given thread.
Action
List modelsLists the models currently available to your account.
Action
List runsReturns a list of runs belonging to a thread.
Action
List run stepsReturns a list of run steps belonging to a run.
Action
List vector store file batch filesReturns a list of vector store files in a batch.
Action
List vector store filesReturns a list of vector store files.
Action
OpenAI agent messageRuns one AI agent turn on OpenAI and returns the model's reply. The turn is billed to the OpenAI account connected on this step, and the agent can call the account's AI tool automations.
Action
Retrieve responseRetrieves a previously created model response by its Response ID.
Action
Search vector storeSearch a vector store for relevant chunks based on a query and filter.
Action
Send model a messageSends a message to an OpenAI model via the Responses API and emits its response. Returns a Response ID usable as previous_response_id for multi-turn conversations.
Action
Submit tool outputs to runSubmit tool outputs when a run requires action.
Action
Transcribe audioTranscribes audio into the input language.
Action
Translate audioTranslates audio into English.
Action
Update assistantModifies an assistant.
Action
Update messageModifies a message.
Action
Update runModifies a run.
Action
Update threadModifies a thread.
Action
Update vector storeModifies a vector store.
Action
Update vector store file attributesUpdate attributes on a vector store file.
Action
Upload fileUpload a file that can be used across various endpoints.
Trigger
New Internal NoteFires when an internal note is added to a Trengo ticket.
Trigger
New Outbound MessageTriggers when an outbound message is created.
Trigger
Ticket Label AddedTriggers when a label is added to a conversation.
Action
Add internal note to ticketAdds an internal note (visible only to agents) to a Trengo ticket.
Action
Add ticketCreate a new support ticket.
Action
Add ticket labelAttaches an existing label to a Trengo ticket.
Action
Create a ContactCreates a contact on a Trengo channel. If a contact with the same identifier already exists on that channel, Trengo returns the existing contact instead of creating a duplicate.
Action
Create webhookSubscribes a URL to one Trengo webhook event type. Used by Trengo instant triggers to register their delivery URL on activation.
Action
Delete contactDelete a contact by id.
Action
Delete ticketDelete a ticket by id.
Action
Find a ContactReturns the Trengo contacts that match the search term.
Action
Get contactRetrieve a single Trengo contact by its id.
Action
Get webhookFetches a webhook by ID, including the event it listens for, the address it sends to and its signing secret. An error occurs if the webhook is not found.
Action
List contactsList all contacts.
Action
List labelsLists the ticket labels defined in the Trengo account (first page).
Action
List ticketsReturns all tickets the connected user is authorized to see, optionally filtered by status, contact, users, channels, labels, last message type or update time.
Action
Send a MessageSends a reply message on an existing Trengo ticket, over the ticket's own channel.
Action
Update contactUpdate an existing contact by id.
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
OpenAI and Trengo, answered
What can start an automation from OpenAI?
Any of OpenAI's 5 triggers in the catalog, including New batch, New file, New model and New vector store. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Trengo when something happens in OpenAI?
Any of Trengo's 15 actions, including Create a Contact, Create webhook, Send a Message and Update contact. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Trengo to OpenAI?
Yes. When something happens in Trengo, your agent can act in OpenAI too. This page covers both directions: Trengo's triggers and OpenAI's actions are listed here as well.
Do I have to build a connector for OpenAI or Trengo?
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.
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.