Together AI MCP, Ready to Go
Run Llama 3.3 and Flux models with Together AI MCP. Connect to Claude or Cursor to handle high-scale inference and fine-tuning for AI agents.
No credit card required. Experience the power of this integration risk-free.
Run Llama 3.3 and Flux models for high-scale production inference.
Works with every AI agent you already use
…and any MCP-compatible client
How fast is the Together AI MCP Server?
Average time for the server to become ready for requests over the last 14 days, measured until the initialize / tools/list handshake completes. Metrics are updated daily between 00:00 and 04:00 UTC. Create a free account, use this MCP on Vinkius Cloud, and connect it to your AI agent in seconds.
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What AI agents can do with Together AI MCP: 27 Tools for Open-Source Inference
Use 27 tools to manage models, generate media, and run batch jobs through the Together AI inference cloud.
Create audio speech
Turn text into spoken audio. It's great for making your AI agent talk.
Create audio transcription
Turn audio files into text. Use this to get transcripts with speaker IDs.
Cancel batch
Stop a batch job that's running. This helps if you need to kill a task early.
Create chat completion
Get a response from a chat model. Use this for standard conversational AI tasks.
Create batch
Start an asynchronous batch job. This is the way to handle large volumes of data at once.
Create endpoint
Set up a dedicated endpoint. Use this when you need consistent, predictable performance.
Create fine tune
Start a new fine-tuning job. This lets you train a model on your specific data.
Delete endpoint
Remove a dedicated endpoint. Use this to clean up your resources when you're done.
Delete file
Remove an uploaded file. This keeps your storage clean after a job is finished.
Delete fine tune
Delete a finished fine-tuning job. This helps manage your active training projects.
Create embeddings
Turn text into vector numbers. This is how you build a search system for your documents.
Get batch
Check the status of a batch job. Use this to see if your large task is finished.
Get endpoint
See the details of a dedicated endpoint. This helps you monitor your custom hardware setup.
Get file
See the metadata for a specific file. Use this to check if your upload was successful.
Get fine tune
Check the progress of a fine-tuning job. This lets you see how your training is going.
Create image generation
Create an image from a text prompt. Use this for generating visual content on the fly.
List endpoints
See all your dedicated endpoints. This helps you keep track of your active hardware.
List files
See all the files you've uploaded. Use this to manage your training data.
List fine tune checkpoints
See the progress points for a fine-tune job. This is useful for monitoring training.
List fine tunes
See all your current fine-tuning jobs. This gives you a bird's eye view of your training.
List models
See all the models available on Together AI. Use this to find the best model for your task.
Create rerank
Reorder search results by relevance. This makes your search systems much more accurate.
Create text completion
Get text based on a prompt. Use this for simple completions without a full chat history.
Update endpoint
Start, stop, or scale a dedicated endpoint. This gives you control over your performance.
Upload file
Send a file to the cloud. Use this to provide data for fine-tuning or batch jobs.
Create video generation
Make a video from a prompt or image. This is the way to generate motion content.
List batches
See all your active batch jobs. This helps you manage your asynchronous workloads.
One MCP enables access. Vinkius turns MCPs into production-ready infrastructure.
You're looking at one of 5,700+ managed MCPs. The real value isn't the catalog. It's the control plane that secures, governs, audits, and manages every interaction between your agents and the tools they use.
No Shadow AI
Every agent action is visible, approved, and auditable. Nothing runs outside your governance.
Absolute agent control
Fine-grained permissions for every agent, MCP, and tool. Instantly revoke access and audit every execution.
Cost control per token
Spend broken down to the token, tool, and agent. Budgets and hard limits. No surprise invoices.
Managed & monitored infra
We operate the runtime, authentication, scaling, retries, and monitoring. Your team manages AI, not infrastructure.
Data protection, DLP by design
Sensitive data is filtered before reaching the model. Access is governed so agents receive only the information they're allowed to use.
Token optimization, real savings
Lower AI costs by delivering the right context instead of unnecessary tools. Better accuracy, faster responses, and fewer wasted tokens.
Together AI MCP for High-Scale Open-Source Model Inference
This is for the AI engineer who needs to scale production models without buying GPUs, or the data scientist who needs to fine-tune models on custom datasets without a DevOps team.
AI Engineer
Running production inference for web apps using Llama 3.3.
Data Scientist
Fine-tuning models on private data and managing checkpoints.
Product Manager
Prototyping image and video generation features for a new app.
Frequently Asked Questions
Can I use Together AI MCP to run Llama 3.3? +
Yes. You can use this MCP to run Llama 3.3 directly through your AI agent for high-quality chat and text completion tasks.
How does Together AI MCP handle image generation? +
It connects you to models like Flux and Stable Diffusion, allowing your agent to turn text prompts into high-quality images instantly.
Can I use Together AI MCP for batch processing? +
Yes. You can use the batch tools to handle large-scale, asynchronous workloads like processing thousands of text completions at once.
Does Together AI MCP support fine-tuning? +
Yes. This MCP allows you to manage your own fine-tuning jobs, create jobs, and monitor checkpoints for your custom models.
Can I use Together AI MCP to build a RAG system? +
Absolutely. You can use it to generate vector embeddings and reorder your search results to build a high-performance retrieval system.
How do I get predictable performance with Together AI MCP? +
You can set up dedicated endpoints through this MCP to ensure consistent performance for your production applications.
How do I generate a chat response using a specific model like Llama 3.3? +
Use the create_chat_completion tool. Specify the model name (e.g., 'meta-llama/Llama-3.3-70B-Instruct-Turbo') and provide an array of messages. The agent will return the generated response from the model.
Can I create images from text prompts with this server? +
Yes! Use the create_image_generation tool. You can specify the model, the prompt description, and optional parameters like width, height, and steps to get high-quality visual outputs.
How can I check the status of my asynchronous batch jobs? +
You can use list_batches to see all your current batch jobs or get_batch with a specific Job ID to retrieve detailed status and results for a particular task.
Your AI, connected to everything.
No credit card required · Free tier available
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