Together AI MCP server. Run Together AI chat, embeddings and images; manage fine-tunes, batches and endpoints.
Add to your MCP config, then reload & authorize:
{
"mcpServers": {
"together-ai": {
"url": "https://together-ai.usefulapi.io/mcp"
}
}
}| Tool | Type | What it does |
|---|---|---|
together_whoami | read | Who am I Identify the API key: its organization, project and project slug. The project slug forms the `<project_slug>/<endpoint_slug>` model name for dedicated-endpoint inference. A cheap way to confirm the key works. Together: GET /whoami. |
together_list_models | read | List models List Together's models with type (chat, language, code, image, embedding, moderation, rerank), context length, organization, license and per-token pricing. Together: GET /models. |
together_list_files | read | List files List uploaded data files (fine-tune, eval and batch-api inputs, plus job outputs) with size, type, purpose and validation status. Together: GET /files. |
together_get_file | read | Get one file Fetch one file's metadata, including its processing_status and validation_report (why a fine-tune training file was rejected). Together: GET /files/{id}. |
together_list_fine_tunes | read | List fine-tuning jobs List fine-tuning jobs with status, base model, output model name and training settings. Together: GET /fine-tunes. |
together_get_fine_tune | read | Get one fine-tuning job Fetch one fine-tuning job: status, progress, hyperparameters, token counts, cost and the output model name. Together: GET /fine-tunes/{id}. |
together_list_fine_tune_events | read | List a fine-tuning job's events List the event log of one fine-tuning job (queued, started, checkpoint saved, epoch completed, errors). The first place to look when a job failed. Together: GET /fine-tunes/{id}/events. |
together_list_batches | read | List batch jobs List batch inference jobs with status, progress, model and input/output/error file ids. Together: GET /batches. |
together_get_batch | read | Get one batch job Fetch one batch job: status (VALIDATING, IN_PROGRESS, COMPLETED, FAILED, EXPIRED, CANCELLED), progress, and the output_file_id / error_file_id once done. Together: GET /batches/{id}. |
together_list_endpoints | read | List endpoints List endpoints with model, owner and state (PENDING, STARTING, STARTED, STOPPING, STOPPED, ERROR). Use mine=true and type=dedicated to see what is running on your account and billing by the minute. Together: GET /endpoints. |
together_get_endpoint | read | Get one endpoint Fetch one dedicated endpoint: state, model, hardware, autoscaling bounds and display name. Together: GET /endpoints/{endpointId}. |
together_list_hardware | read | List hardware List hardware configurations for dedicated endpoints with GPU type/count/memory and price in cents per minute. Pass a model to get only compatible configurations with live availability. Together: GET /hardware. |
together_list_evaluations | read | List evaluation jobs List LLM-as-a-judge evaluation jobs (classify, score, compare) with status, parameters and results once completed. Together: GET /evaluation. |
together_chat_completion | write | Chat completion Run a chat completion on a Together model (billed per token). Non-streaming. For a dedicated endpoint pass its `<project_slug>/<endpoint_slug>` as the model. Together: POST /chat/completions. |
together_create_embeddings | write | Create embeddings Generate vector embeddings for one or more texts (billed per token). Together: POST /embeddings. |
together_generate_image | write | Generate an image Generate images from a prompt (billed per image/megapixel). Returns image URLs by default rather than base64, to keep responses small. Together: POST /images/generations. |
together_create_fine_tune | write | Create a fine-tuning job Start a fine-tuning job on an uploaded training file (billed per token processed). Stop it with together_cancel_fine_tune. Together: POST /fine-tunes. |
together_cancel_fine_tune | write | Cancel a fine-tuning job Cancel a running fine-tuning job. Cannot be resumed, but a new job can continue from its last checkpoint via from_checkpoint. Together: POST /fine-tunes/{id}/cancel. |
together_create_batch | write | Create a batch job Start an asynchronous batch job over an uploaded JSONL input file (purpose batch-api), at a discount to real-time inference. Together: POST /batches. |
together_cancel_batch | write | Cancel a batch job Cancel a batch job that has not finished. Together: POST /batches/{id}/cancel. |
together_create_endpoint | write | Create a dedicated endpoint Deploy a model on dedicated GPUs. The endpoint STARTS AUTOMATICALLY and bills per minute of uptime until stopped — set inactive_timeout to auto-stop it, and use together_list_hardware for valid hardware ids. Together: POST /endpoints. |
together_start_endpoint | write | Start a dedicated endpoint Start a stopped dedicated endpoint. It bills per minute of uptime until stopped. Reversible with together_stop_endpoint. Together: PATCH /endpoints/{endpointId} with state=STARTED. |
together_stop_endpoint | write | Stop a dedicated endpoint Stop a running dedicated endpoint, which stops its per-minute billing. Requests to it fail until it is started again. Together: PATCH /endpoints/{endpointId} with state=STOPPED. |
together_ai_usage_status | Usage status (free-tier meter) Report the caller's current free-tier usage this month: calls used, monthly limit, remaining, and whether the cap is reached. Read-only; does not count against the meter. | |
together_ai_upgrade | Upgrade to Pro (unlimited) Subscribe to the Pro plan for UNLIMITED Together AI tool calls (the free tier caps monthly usage). Choose monthly ($9/month) or yearly ($90/year — 2 months free) billing. Returns a Stripe Checkout link to open in your browser; after payment your account upgrades automatically. Read-only; does not count against the meter. |
| Plan | Price | Limit |
|---|---|---|
| Free | $0 | 100 tool calls / month |
| Proper user | $9/mo · $90/yr | Unlimited |
This is a Model Context Protocol endpoint — meant to be connected from an AI client, not opened in a browser. An invalid_token response at the URL is the auth gate working as designed; clients authenticate automatically.