Compares model pricing and limits, creates assistants and threads, drives runs and submits tool outputs, and checks on batch and video jobs.
30actions available
Every action runs live through MCP. Nothing to build, nothing to maintain.
Ayro adds a response to an ongoing conversation thread, keeping the customer dialog flowing. The message gets logged for full conversation history and context preservation.
Ayro starts a dedicated conversation channel for each customer inquiry, organizing interactions from first message to resolution. This keeps separate issues from tangling together.
Ayro generates an AI response by submitting a query to an LLM, returning a complete answer ready to send. This powers intelligent, contextual replies mid-conversation.
Each card is one request a support team gets, and the Ai ml api actions Ayro runs to close it.
Ayro lists what the account can call and pulls each model's pricing, features, and context limits alongside the current billing balance, so the choice is made against real numbers rather than a default.
Ayro creates the assistant with its model and instructions, opens the thread it will work in, and adds the first message, so a new assistant is ready to run in one exchange.
Ayro starts the run, hands back results when it pauses waiting on a tool, and reads the step trail to see where it got to, so a stalled run is diagnosed instead of retried blindly.
Ayro reads the status of batch processing jobs and fetches Luma video generations by ID once they complete, so long-running work is collected on a later turn rather than blocked on.
How it works
Connect once, then just ask. There is no workflow builder to learn and nothing to maintain — Ayro reads the Ai ml api actions it has and picks the ones a request needs.
Authorize the Ai ml api account your team already uses — one consent screen, no API keys, no mapping tables. Ayro can only do what you granted that account, and you can disconnect it at any time.
Describe the job the way you would hand it to a teammate. Ayro maps it to the Ai ml api actions that close it and chains as many as the request needs.
The agent runs the actions inside the conversation the customer is already in, so nobody copies data between tabs and your team can take over at any point.
Get started freeAi ml api · Ayro
What can you do in Ai ml api without me setting anything up?
These, right away:
Great, let's start with the first one.
FAQ
Setup, permissions, and the limits of what Ayro can do inside Ai ml api.
Yes. List Models With Details returns pricing, features, and context limits next to each model, which is the difference between choosing a model deliberately and discovering its cost on an invoice. Get Billing Balance reports what the account has left, so both halves of that decision are available in the same conversation.
All 30 actions your agent can call on Ai ml api, straight from the live MCP connection.
Cancel a run that is currently in progress.
Create an AI assistant with configurable model, instructions, and tools.
Create a new message in a thread.
Create a run that executes an assistant on a thread.
Create a new thread for conversation with an assistant.
Delete an assistant by ID.
Delete a specific message from a thread.
Delete a thread by its ID.
Retrieve details of a specific assistant by ID.
Retrieve the current billing balance for the account.
Fetch Luma AI video generation results by generation IDs.
Retrieve information about a specific message by its ID.
Retrieve a previously generated model response by its unique ID.
Retrieve a specific run by ID from a thread.
Retrieve a specific run step by its ID within a thread and run.
Retrieve information about a specific thread by ID.
List all assistants associated with the account.
Get the status or results of a batch processing job.
Fetch user's Luma AI video generations.
Retrieve a list of messages from a specific thread.
List all available AI models from the AI/ML API.
List all available AI/ML models with detailed information including pricing, features, and capabilities.
List all runs for a specific thread.
List the steps in a run.
Submit tool outputs for a run that requires action.
Generate text completions or chat responses using a specified LLM model.
Modify an existing assistant's properties including name, instructions, model, and tools.
Modify metadata for a specific message in a thread.
Update a run's metadata with key-value pairs.
Update thread metadata and tool resources in the AI/ML API.
Same connection, same setup. Pick the next one your team already uses.
Searches Trello cards semantically, lists the tables in an Airtable base, validates an IBAN, and pushes a prepared deal record in.
Reports deployment accuracy and drift, starts Autopilot runs, queues batch predictions, and keeps datasets linked to the right use case.
Runs OCR and image annotation over pictures and PDFs, builds the Product Search catalogue, and polls long-running batch operations.
Fetches the parsed text and metadata for Metaphor documents by ID, several at a time, turning a set of result IDs into readable content.
Submits recordings for transcription, returns transcripts and SRT or VTT captions, and maintains the custom vocabulary behind accuracy.
Detects the language of a message, flags abuse types and sentiment, scores text similarity, and paraphrases or translates a passage.

Authorize the account and your agent has all 30 actions from the first conversation.
