OpenAI Alternative MCP Server
Manage OpenAI resources via API — list models, monitor fine-tunes, manage batches and inspect Assistants from any AI agent.
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What is the OpenAI Alternative MCP Server?
The OpenAI MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to OpenAI. Manage OpenAI resources via API — list models, monitor fine-tunes, manage batches and inspect Assistants from any AI agent. Powered by the Vinkius AI Gateway — no API keys, no infrastructure, connect in under 2 minutes.
OpenAI MCP Server: see your AI Agent in action
Built-in capabilities (13)
cancel_batch
Partially completed requests may still be processed. Provide the batch ID. Cancel a running batch job
cancel_fine_tune
The job status will change to "cancelled". Provide the fine-tune job ID. This is useful if you uploaded the wrong training file or want to stop a long-running job. Cancel a running fine-tuning job
create_batch
Requires the input file ID (containing JSONL requests) and the endpoint (e.g. "/v1/chat/completions"). Optionally set the completion window ("24h" default). Returns the batch with its ID for tracking. Create a new batch processing job
delete_file
Provide the file ID from list_files. WARNING: this action is irreversible and will break any fine-tunes or assistants using this file. Delete an uploaded file from OpenAI
get_assistant
Provide the assistant ID. Get details for a specific OpenAI Assistant
get_batch
Provide the batch ID. Get details for a specific batch job
get_fine_tune
Provide the fine-tune job ID. Get details for a specific fine-tuning job
get_model
g. "gpt-4o", "gpt-4o-mini", "text-embedding-3-small", "dall-e-3", "whisper-1"). Returns the model ID, owner organization, creation date and permission flags. Use this to verify a model exists and check its metadata before using it. Get details for a specific OpenAI model
list_assistants
Each Assistant shows its ID, name, instructions, model, tools (code interpreter, file search, function calling) and creation date. Use this to audit your Assistant configurations. List OpenAI Assistants
list_batches
Batches allow you to process many API requests at once at a lower cost. Each batch shows its ID, status (validating, in_progress, finalizing, completed, failed, expired, cancelled), input/output file IDs and request counts. List batch processing jobs
list_files
Files are used for fine-tuning, Assistants API and batch processing. Each file shows its ID, filename, purpose (fine-tune, assistants, batch), size and status. Optionally filter by purpose. List files uploaded to OpenAI
list_fine_tunes
Each job shows its ID, status (validating_files, queued, running, succeeded, failed, cancelled), base model, training file, created date and estimated finish time. Use this to monitor your fine-tuning pipeline. List fine-tuning jobs
list_models
5, DALL-E, Whisper, Embedding and fine-tuned models. Each model returns its ID, owned_by (organization), creation date and permissions. Use this to discover which models are available for your account and their capabilities. List all available OpenAI models
What this connector unlocks
Connect your OpenAI account to any AI agent and take full control of your AI resources through natural conversation.
What you can do
- Model Discovery — List all available models (GPT-4, GPT-3.5, DALL-E, Whisper, Embeddings) with ownership and capability info
- File Management — Browse, manage and delete uploaded files used for fine-tuning and Assistants
- Fine-Tuning — Monitor fine-tuning jobs, check status (running, succeeded, failed) and cancel long-running jobs
- Batch Processing — Create, track and cancel batch jobs for cost-effective bulk API processing
- Assistant Management — List and inspect configured Assistants with their models, tools and instructions
How it works
1. Subscribe to this server
2. Enter your OpenAI API Key
3. Start managing your AI resources from Claude, Cursor, or any MCP-compatible client
No more switching to the OpenAI dashboard to check fine-tune status or manage batch jobs. Your AI acts as a dedicated ML ops assistant.
Who is this for?
- ML Engineers — monitor fine-tuning jobs, track batch processing and manage model files without leaving your IDE
- DevOps — audit uploaded files, review batch statuses and clean up unused resources
- Product Teams — discover available models, inspect Assistant configurations and review resource usage
Frequently asked questions
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