Openai MCP server

Connect Openai to Claude, ChatGPT, Cursor, Claude Code, Codex, Gemini, GitHub Copilot and any other MCP client, for your whole team. Metorial adds security, governance, and tracing, and gives everyone one Magic MCP URL to connect.

What you can do with the Openai MCP server

Ask your agent in plain language. Each of these maps to a real tool on the server.

  • Use the list files tool in Openai
  • Use the list models tool in Openai
  • Use the delete vector store tool in Openai
  • Use the create embeddings tool in Openai
  • Use the generate text tool in Openai
  • Use the create batch tool in Openai

Supported Tools

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.

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.

Connect Openai to your AI client

Every client uses the same Magic MCP URL, and so does any other MCP client. Add it once and sign in with SSO.

  1. Enable Openai in Metorial. In your Metorial portal, enable the Openai MCP server and sign in with the account that owns the data. Access stays governed by your team policies.
  2. Add a custom connector. Open Customize, then Connectors. Select Add, then Custom, then Web.
  3. Paste your Metorial MCP URL. Name it Metorial, paste your Magic MCP URL (<your-magic-mcp-url>) and continue.
  4. Sign in. Select Add and sign in to load Openai tools.

Run Openai through the Metorial gateway

One governed layer for every app your agents reach, not a separate connector per tool.

  • Give Openai and every other app to your whole team through one MCP gateway, behind your SSO.
  • Scope which teams and agents can use Openai tools with role-based access control, and trace every call.
  • Prefer to run it yourself? Metorial is open source and self-hostable.

More integrations teams use with Openai

Notion

Create, read, update, and archive pages and databases in a Notion workspace. Manage blocks (paragraphs, lists, headings, embeds, etc.) within pages. Query databases with filters and sorts across rich property types including text, numbers, dates, selects, relations, and formulas. Search across pages and databases by title. Add and read comments on pages and blocks. Upload files to pages. Manage workspace users and retrieve user profiles.

Google Sheets

Create, read, and update spreadsheets and their cell data. Read and write values to individual cells, ranges, or multiple ranges using A1 notation or named ranges. Apply cell formatting including text styles, backgrounds, borders, number formats, and conditional formatting. Manage sheets (tabs) within a spreadsheet—add, delete, copy, rename, and reorder them. Create and manage embedded charts, pivot tables, filter views, data validation rules, protected ranges, named ranges, and merged cells. Perform batch operations to apply multiple updates atomically.

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.

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. Manage org metadata including custom objects, fields, layouts, and workflows. Query data using GraphQL for precise data retrieval across related objects.

Sharepoint

Manage SharePoint sites, document libraries, lists, and files. Create, read, update, and delete lists and list items with custom columns. Resolve site users to numeric Person/Group LookupId values. 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. Retrieve site properties and search for sites across Microsoft 365.

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.

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.

  1. How many tools does the Openai MCP server have?
    The Openai MCP server exposes 34 tools, including List Files, List Models, Delete Vector Store. Each one is governed and traced through Metorial.
  2. Openai exposes tools your agents call on demand; it does not publish event triggers yet. Everything still runs through one governed MCP URL.
  3. Any MCP client, including VS Code, Windsurf, Zed, OpenCode and Grok. Each one reaches the Openai MCP server through the same Metorial URL.
  4. Use role-based access control to decide which teams, users, and agents can use Openai and which of its tools they can call.
  5. Yes. Metorial is open source, so you can run the Openai MCP server yourself or use the hosted gateway.

Connect Openai to production AI agents

See how Metorial gives your team governed access to Openai, with tracing and security controls built in.