list_files
List Files
List files uploaded to OpenAI, optionally filtered by purpose (e.g. "fine-tune", "assistants"). Returns file metadata including ID, name, size, and purpose.
Supported Tools
list_models
List Models
List all available OpenAI models, or retrieve details about a specific model. Useful for discovering available model IDs, owners, and capabilities before making API calls.
delete_vector_store
Delete Vector Store
Delete a vector store by its ID. This permanently removes the store and its indexed data.
create_embeddings
Create Embeddings
Generate vector embeddings for text input using OpenAI embedding models (text-embedding-3-small, text-embedding-3-large). Useful for search, RAG, clustering, and semantic similarity. Supports configurable output dimensions.
generate_text
Generate Text
Generate text using OpenAI chat completion models (GPT-5, GPT-4o, etc.). Supports multi-turn conversations, system instructions, structured JSON output, and configurable generation parameters.
create_batch
Create Batch
Submit a batch of API requests for asynchronous processing at reduced cost. Supports Responses, chat completions, embeddings, completions, and moderations endpoints. The input must be a JSONL file uploaded via the Files API.
create_response
Create Response
Generate a response using the OpenAI Responses API, the primary gateway for all model families. Supports text generation, built-in tools (web search, file search, code interpreter), function calling, structured output, and reasoning models with configurable effort levels.
moderate_content
Moderate Content
Classify text against OpenAI's content policy categories. Returns flagged status and per-category scores for hate, harassment, self-harm, sexual, and violence content. Useful for filtering harmful content in user-generated input.
get_file
Get File
Retrieve metadata for a specific file by its ID. Returns file details including name, size, purpose, and status.
get_fine_tuning_job
Get Fine-Tuning Job
Retrieve the status and details of a fine-tuning job, or list all fine-tuning jobs. Includes training metrics, timestamps, and the resulting fine-tuned model name.
cancel_batch
Cancel Batch
Cancel a batch processing job that is in progress. Already-completed requests within the batch will still be available.
create_vector_store
Create Vector Store
Create a managed vector store for uploading, chunking, and searching files. Vector stores power file search in the Responses API and support hybrid search (semantic + keyword).
search_vector_store
Search Vector Store
Search a vector store using natural language queries. Returns ranked results with relevance scores. Supports configurable result limits and score thresholds.
list_vector_stores
List Vector Stores
List all vector stores in your OpenAI project. Returns store metadata, file counts, and status information.
delete_file
Delete File
Delete a file from your OpenAI account by its ID. The file will no longer be available for use with fine-tuning, vector stores, or other features.
create_fine_tuning_job
Create Fine-Tuning Job
Create a new fine-tuning job to customize an OpenAI model on your training data. Supports supervised fine-tuning and direct preference optimization (DPO). Configure hyperparameters such as epochs, batch size, and learning rate.
get_batch
Get Batch
Retrieve the status and details of a batch processing job, or list all batches. Returns processing progress, output file IDs, and error information.
cancel_fine_tuning_job
Cancel Fine-Tuning Job
Cancel a running fine-tuning job. The job must be in a cancellable state (e.g. "validating_files" or "running").
generate_image
Generate Image
Generate images from text prompts using OpenAI's image generation models (e.g. DALL·E 3, gpt-image-1). Returns generated image content as Slate attachments when the API returns base64 data. Supports configurable size, quality, and style.
list_response_input_items
List Response Input Items
List the input items used to create a stored OpenAI response.
add_vector_store_file
Add Vector Store File
Attach an uploaded OpenAI file to a vector store so it can be indexed for file search.
translate_audio
Translate Audio
Translate speech from an uploaded audio file into English text.
get_vector_store_file_content
Get Vector Store File Content
Retrieve parsed content chunks for a file attached to a vector store.
delete_response
Delete Response
Delete a stored OpenAI response by ID.
remove_vector_store_file
Remove Vector Store File
Detach a file from a vector store. This removes it from the vector store index but does not delete the uploaded file.
get_vector_store_file
Get Vector Store File
Retrieve status and metadata for one file attached to a vector store.
get_file_content
Get File Content
Retrieve the raw content of an uploaded OpenAI file, such as JSONL batch output, fine-tuning data, or uploaded text.
list_vector_store_files
List Vector Store Files
List files attached to a vector store, optionally filtered by processing status.
upload_file
Upload File
Upload a file to OpenAI for use with batch processing, fine-tuning, vector stores, vision, or user data workflows. Accepts plain text content or base64-encoded bytes.
get_response
Get Response
Retrieve a stored OpenAI response by ID, including status, model output items, and token usage.
get_vector_store
Get Vector Store
Retrieve details for a specific OpenAI vector store, including processing status and file counts.
synthesize_speech
Synthesize Speech
Generate spoken audio from text using OpenAI text-to-speech models.
update_vector_store
Update Vector Store
Update a vector store name, expiration policy, or metadata.
transcribe_audio
Transcribe Audio
Transcribe speech from an uploaded audio file into the source language text.
More integrations teams use with Openai
GitHub
Manage repositories, issues, and pull requests. Create and configure branches, star repositories, review code, and merge changes. Automate CI/CD workflows with GitHub Actions, manage workflow runs, secrets, and artifacts. Track issues with labels, milestones, and assignees. Search across code, repositories, issues, and users. Manage organizations, teams, and memberships. Create and manage projects, gists, packages, deployments, and environments. Access security alerts including code scanning, secret scanning, and Dependabot alerts. Read and write file contents in repositories. Manage webhooks, notifications, and codespaces.
Sharepoint
Manage SharePoint sites, document libraries, lists, and files. Create, read, update, and delete lists and list items with custom columns. Upload, download, move, copy, and version files in document libraries. Search across sites, files, folders, lists, and list items using Microsoft Search. Manage permissions at site, list, and item levels with granular access control. Define and manage content types and site columns. Subscribe to webhooks for list and library change notifications. Retrieve site properties and search for sites across Microsoft 365.
Salesforce
Manage CRM data including Accounts, Contacts, Leads, Opportunities, Cases, and custom objects. Create, read, update, and delete records. Query data using SOQL and search across objects using SOSL. Perform bulk data operations for large-scale imports, exports, and migrations. Execute composite requests to batch multiple operations in a single API call. Access analytics, reports, and dashboards. Manage files and attachments associated with records. Interact with Chatter feeds, posts, and groups for social collaboration. Subscribe to real-time change events via Change Data Capture and Platform Events. Manage org metadata including custom objects, fields, layouts, and workflows. Query data using GraphQL for precise data retrieval across related objects.
Airtable
Create, read, update, and delete records in Airtable bases and tables. Manage base schemas including creating tables and fields. Filter records using formulas, sort by fields, and scope queries to specific views. Upsert records to find, create, or update in a single call. Upload attachments to records, read and write record comments, list accessible bases, and receive real-time base change events through webhooks.
Confluence
Create, read, update, and delete pages, blog posts, comments, and attachments in Confluence spaces. Manage spaces, permissions, labels, and content restrictions. Search content using Confluence Query Language (CQL). Upload and download file attachments with versioning. Manage users, groups, and group memberships. Create and manage whiteboards, databases, folders, and templates. View and update inline tasks. Access audit logs. Listen for webhooks on page, blog, comment, attachment, space, label, and user events.
Bitbucket
Manage Git repositories, pull requests, and CI/CD pipelines on Bitbucket Cloud. Create, fork, and configure repositories within workspaces and projects. Create, review, approve, merge, and decline pull requests with inline code comments. Browse source code, list commits, and manage branches and tags. Track issues with the built-in issue tracker. Trigger, monitor, and manage Bitbucket Pipelines. List workspace members, configure repository default reviewers and branch restrictions, create and manage repository webhooks, and search code across repositories.
How to use Openai on Metorial
Auto-Generate OpenAI Embeddings for SharePoint Documents to Power Search
The agent scans a SharePoint document library for new or recently updated files, extracts their text content, generates embeddings via OpenAI, and stores them in a vector store to enable semantic search across the knowledge base.
Moderate and Classify Discord Community Messages with OpenAI Content Moderation
The agent monitors Discord channels for new messages, runs them through OpenAI content moderation, automatically removes policy-violating content, and logs flagged events to a moderation audit thread.
Technical notes for Openai
Generate text, images, audio, and video using large language models and multimodal AI. Create chat completions, generate and edit images from text prompts, convert text to speech, transcribe and translate audio, generate video, and create text embeddings for search and retrieval. Fine-tune models on custom training data, run evaluations to measure model performance, and moderate content against policy categories. Manage vector stores for semantic file search, upload and organize files, and submit batch processing jobs for asynchronous bulk requests. Conduct real-time speech-to-speech conversations via WebRTC or SIP. Administer organizations, projects, users, API keys, and audit logs programmatically. Receive webhook notifications for background responses, batch jobs, fine-tuning jobs, eval runs, and incoming realtime calls.
Frequently asked questions
Common questions about connecting Openai to AI agents with Metorial.
Can Metorial connect Openai to AI agents?
Yes. Metorial connects AI agents to Openai through a governed integration layer, so teams can use the provider while keeping access controlled and observable.Does the Openai integration work with MCP?
Metorial is MCP compatible and lets teams expose approved provider tools to MCP-capable agents and clients through a controlled access layer.How does Metorial control access to Openai?
Metorial applies policies across users, groups, providers, agents, and individual tools, then records the context around every agent interaction.Can teams trace Openai activity from agents?
Yes. Metorial records provider activity so teams can inspect tool calls, troubleshoot integrations, and give security teams the visibility they need.