Together AI Connector for AI agents.

27 live capabilities

Run Llama 3.3 and Flux models for high-scale production inference.

Live agent request Together AI / Connector

Waiting for input…

AI Agent

Why people use Together AI

Together AI for High-Scale Open-Source Model Inference

This Connector changes that by giving you a direct line to the Together AI inference cloud. You can call Llama 3.3 or Flux directly through your agent without ever touching a server. You get production-grade performance and the ability to scale instantly, letting you focus on your app instead of your infrastructure.

What Vinkius changes

You get instant access to a massive library of open-source models without managing a single server.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

Real-world use case 01

Building a custom chatbot

A dev asks their agent to use create_chat_completion with Llama 3.
Real-world use case 02

Generating marketing assets

A social media manager asks the agent to use create_image_generation to make 50 unique product photos.
Real-world use case 03

Processing large datasets

A researcher uses create_batch to run a text completion on 10,000 rows of data overnight.

Complete set · 27capabilities

The complete Together AI capability set.

These are the exact actions your AI can choose when you ask it to work with Together AI.

Capability set01 / 07

01—04

4 capabilities in this set.

Part of 27 available through Together AI.

01 Capability
Cancel batch
Stop a batch job that's running. This helps if you need to kill a task early.
02 Capability
Create chat completion
Get a response from a chat model. Use this for standard conversational AI tasks.
03 Capability
Create batch
Start an asynchronous batch job. This is the way to handle large volumes of data at once.
04 Capability
List fine tunes
See all your current fine-tuning jobs. This gives you a bird's eye view of your training.

Capability set02 / 07

05—08

4 capabilities in this set.

Part of 27 available through Together AI.

05 Capability
Create audio speech
Turn text into spoken audio. It's great for making your AI agent talk.
06 Capability
Create audio transcription
Turn audio files into text. Use this to get transcripts with speaker IDs.
07 Capability
Create endpoint
Set up a dedicated endpoint. Use this when you need consistent, predictable performance.
08 Capability
Create fine tune
Start a new fine-tuning job. This lets you train a model on your specific data.

Capability set03 / 07

09—12

4 capabilities in this set.

Part of 27 available through Together AI.

09 Capability
Delete endpoint
Remove a dedicated endpoint. Use this to clean up your resources when you're done.
10 Capability
Delete file
Remove an uploaded file. This keeps your storage clean after a job is finished.
11 Capability
Delete fine tune
Delete a finished fine-tuning job. This helps manage your active training projects.
12 Capability
Create embeddings
Turn text into vector numbers. This is how you build a search system for your documents.

Capability set04 / 07

13—16

4 capabilities in this set.

Part of 27 available through Together AI.

13 Capability
Get batch
Check the status of a batch job. Use this to see if your large task is finished.
14 Capability
Get endpoint
See the details of a dedicated endpoint. This helps you monitor your custom hardware setup.
15 Capability
Get file
See the metadata for a specific file. Use this to check if your upload was successful.
16 Capability
Get fine tune
Check the progress of a fine-tuning job. This lets you see how your training is going.

Capability set05 / 07

17—20

4 capabilities in this set.

Part of 27 available through Together AI.

17 Capability
Create image generation
Create an image from a text prompt. Use this for generating visual content on the fly.
18 Capability
List endpoints
See all your dedicated endpoints. This helps you keep track of your active hardware.
19 Capability
List files
See all the files you've uploaded. Use this to manage your training data.
20 Capability
List fine tune checkpoints
See the progress points for a fine-tune job. This is useful for monitoring training.

Capability set06 / 07

21—24

4 capabilities in this set.

Part of 27 available through Together AI.

21 Capability
List models
See all the models available on Together AI. Use this to find the best model for your task.
22 Capability
Create rerank
Reorder search results by relevance. This makes your search systems much more accurate.
23 Capability
Create text completion
Get text based on a prompt. Use this for simple completions without a full chat history.
24 Capability
Update endpoint
Start, stop, or scale a dedicated endpoint. This gives you control over your performance.

Capability set07 / 07

25—27

3 capabilities in this set.

Part of 27 available through Together AI.

25 Capability
Upload file
Send a file to the cloud. Use this to provide data for fine-tuning or batch jobs.
26 Capability
Create video generation
Make a video from a prompt or image. This is the way to generate motion content.
27 Capability
List batches
See all your active batch jobs. This helps you manage your asynchronous workloads.

Set up in minutes

One URL. Then ask Together AI to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Together AI from the conversation.

Choose your client

Live preview

Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP

https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp

Step 01

Open Connectors

In Claude Web or Claude Desktop, open Settings and choose Connectors.
Step 02

Add the URL

Choose Add custom connector, name it Together AI, and paste the URL above.
Step 03

Turn it on in chat

Select +, open Connectors, and enable Together AI for the conversation.

ChatGPT · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP

https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp

Step 01

Open MCP settings

On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
Step 02

Add the URL

Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Together AI URL.
Step 03

Save and start

Save the connection and enable Together AI in your conversation. Desktop may ask you to restart once.

Cursor · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "together-ai-alternative": {
      "url": "https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp"
    }
  }
}

Step 01

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
Step 02

Add the server config

Paste the JSON configuration above into the mcp.json file that opens
Step 03

Save the file

Cursor will automatically detect the new Connector
Step 04

Start using Together AI

Open Agent mode in chat and ask: "Using Together AI, help me...". 27 tools available

VS Code Copilot · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "together-ai-alternative": {
      "url": "https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp"
    }
  }
}

Step 01

Create MCP config

Create a .vscode/mcp.json file in your project root
Step 02

Add the server config

Paste the JSON configuration above
Step 03

Enable Agent mode

Open GitHub Copilot Chat and switch to Agent mode using the dropdown
Step 04

Start using Together AI

Ask Copilot: "Using Together AI, help me...". 27 tools available

Windsurf · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "together-ai-alternative": {
      "url": "https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp"
    }
  }
}

Step 01

Open MCP Settings

Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Step 02

Add the server

Paste the JSON configuration above into mcp_config.json
Step 03

Save and reload

Windsurf will detect the new server automatically
Step 04

Start using Together AI

Open Cascade and ask: "Using Together AI, help me...". 27 tools available

Cline · IDE configuration

Official guide ↗

Advanced setup

{
  "mcpServers": {
    "together-ai-alternative": {
      "url": "https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp"
    }
  }
}

Step 01

Open Cline MCP Settings

Click the Connectors icon in the Cline sidebar panel
Step 02

Add remote server

Click "Add Connector" and paste the configuration above
Step 03

Enable the server

Toggle the server switch to ON
Step 04

Start using Together AI

Ask Cline: "Using Together AI, help me...". 27 tools available

Claude Code · Terminal command

Official guide ↗

Advanced setup

claude mcp add together-ai-alternative --transport http "https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp"

Step 01

Install Claude Code

Run npm install -g @anthropic-ai/claude-code if not already installed
Step 02

Add the Connector

Run the command above in your terminal
Step 03

Verify the connection

Run claude mcp to list connected servers, or type /mcp inside a session
Step 04

Start using Together AI

Ask Claude: "Using Together AI, show me...". 27 tools are ready

Where the request belongs

Work Together AI can move forward.

Built around the request

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.

01

AI Engineer

Running production inference for web apps using Llama 3.3.

02

Data Scientist

Fine-tuning models on private data and managing checkpoints.

03

Product Manager

Prototyping image and video generation features for a new app.

Build the capability set

Each Connector adds new actions and data without changing how you work.

Browse Connectors

01 10 capabilities

OpenAI

Use GPT-4o, DALL-E 3, embeddings, fine-tuning, and moderation as capabilities inside your AI agent workflows.

02 4 capabilities

DeepInfra (Serverless LLM Inference)

Run top-tier LLMs, image generation, and embeddings via DeepInfra's serverless infrastructure directly from your AI agent.

03 10 capabilities

Forefront

Access Forefront AI models directly from your agent. generate chat completions, manage fine-tuning jobs, and collect LLM outputs with pipelines.

04 19 capabilities

Gradient AI (LLM API & Finetuning)

Access powerful LLMs, fine-tune models on your own data, and generate embeddings directly through your AI agent.

05 5 capabilities

Monster API (Serverless GPU & AI Model Hosting)

Access powerful AI models for image generation, text-to-speech, and transcription via serverless GPU infrastructure.

06 13 capabilities

Eden AI

Access 100+ AI models through a single API. route LLMs, generate embeddings, and execute specialized AI tasks like OCR and translation.

Bring your own AI

Change the model, client or framework. Keep Together AI connected.

Before you connect

Questions about Together AI.

The practical details behind the request, access and result.

Can I use Together AI MCP to run Llama 3.3?

Yes. You can use this Connector 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 capabilities to handle large-scale, asynchronous workloads like processing thousands of text completions at once.

Does Together AI MCP support fine-tuning?

Yes. This Connector 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 Connector 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 capability. 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 capability. 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.

One connection away

Give your agent a direct line to Together AI.

Connect Together AI once. Keep it beside 5,900+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available