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Connect Together AI (Alternative) to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Run high-speed inference and fine-tuning directly from your AI client.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 27 capabilities

We ship only the actions that matter.

Capability set01 / 07

01-04

4 capabilities in this set.

Part of 27 available through Together AI.

  1. 01

    Upload file

    This capability uploads files to the platform for use in fine-tuning, evaluations, or batch inference.

  2. 02

    Create chat completion

    This capability generates a model response for a specific chat conversation.

  3. 03

    Create fine tune

    This capability starts a fine-tuning job using a base model and a training data file.

  4. 04

    Delete endpoint

    This capability removes a dedicated endpoint once it is no longer in use.

Capability set02 / 07

05-08

4 capabilities in this set.

Part of 27 available through Together AI.

  1. 05

    Delete fine tune

    This capability deletes a fine-tuning job that is no longer running.

  2. 06

    Get endpoint

    This capability retrieves the specific details of a dedicated endpoint using its ID.

  3. 07

    Get fine tune

    This capability fetches the details of a specific fine-tuning job.

  4. 08

    List endpoints

    This capability returns a list of all your dedicated endpoints.

Capability set03 / 07

09-12

4 capabilities in this set.

Part of 27 available through Together AI.

  1. 09

    List files

    This capability provides a list of all files you have uploaded.

  2. 10

    List fine tune checkpoints

    This capability retrieves the available checkpoints for a specific fine-tuning job.

  3. 11

    List fine tunes

    This capability shows the status and details of all your fine-tuning jobs.

  4. 12

    List models

    This capability lists all the models available through Together AI.

Capability set04 / 07

13-16

4 capabilities in this set.

Part of 27 available through Together AI.

  1. 13

    Create video generation

    This capability creates videos based on text or image prompts.

  2. 14

    Update endpoint

    This capability modifies the scaling or status of a dedicated endpoint.

  3. 15

    Create audio speech

    This capability generates speech from text using a specific voice model.

  4. 16

    Cancel batch

    This capability stops a running batch job using its ID.

Capability set05 / 07

17-20

4 capabilities in this set.

Part of 27 available through Together AI.

  1. 17

    Get file

    This capability retrieves metadata for a specific uploaded file.

  2. 18

    List batches

    This capability lists all active and completed batch jobs.

  3. 19

    Create audio transcription

    This capability transcribes audio files into text with speaker identification.

  4. 20

    Create batch

    This capability starts a new asynchronous batch job using an input file and a target endpoint.

Capability set06 / 07

21-24

4 capabilities in this set.

Part of 27 available through Together AI.

  1. 21

    Create embeddings

    This capability converts input text into vector embeddings.

  2. 22

    Create endpoint

    This capability sets up a dedicated endpoint with specific hardware configurations.

  3. 23

    Create image generation

    This capability generates images from text prompts with custom dimensions.

  4. 24

    Create rerank

    This capability reorders documents based on their relevance to a search query.

Capability set07 / 07

25-27

3 capabilities in this set.

Part of 27 available through Together AI.

  1. 25

    Create text completion

    This capability generates text completions for a given prompt.

  2. 26

    Delete file

    This capability removes a specific file from your storage.

  3. 27

    Get batch

    This capability retrieves the details of a specific batch job.

Real work

What teams actually run

01

Custom Model Training

Fine-tune a specific model on your own data to handle niche tasks.

02

Automated Content Creation

Generate a series of images or videos based on text descriptions.

03

Advanced Search Systems

Use embeddings and reranking to build highly accurate retrieval systems.

04

Audio Transcription

Convert large audio files into text with speaker identification.

Automate a task

Put Together AI to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Together AI works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Together AI to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

1228ms average. Fast in production.

Together AI is checked daily against the live service.

Daily averagePeak 1397ms
Oct 3Today
Fastest day
908ms
Slowest day
1397ms
14-day trend
Improving-5%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 27 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Together AI, so you can see the experience inside your AI.

It does not authenticate your account with Together AI. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Together AI Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Together AI capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "together-ai-alternative-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Together AI in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Together AI owners hand off.

This MCP is built for technical users who need high-performance access to open-source model ecosystems.

  • 01

    AI Developers

    They use this to plug LLMs and image models into apps without managing hardware.

  • 02

    Data Scientists

    They use this to fine-tune models on custom datasets and manage checkpoints.

  • 03

    Product Teams

    They use this to prototype and scale AI features using a single API.

FAQ

Questions Together AI owners ask.

  • 01

    What models can I use with this MCP?

    You can access over 100 open-source models, including Llama 3.3, Qwen, Mixtral, and Flux.

  • 02

    Do I need to host the models myself?

    No, the models run on Together AI's inference cloud, so you don't have to manage any infrastructure.

  • 03

    Can I use this for image generation?

    Yes, you can use capabilities like create_image_generation and create_video_generation to make media from text.

  • 04

    How do I handle large amounts of data?

    You can use the Batch API to handle large-scale asynchronous workloads efficiently.

  • 05

    Is fine-tuning supported?

    Yes, you can upload files and create fine-tuning jobs to train models on your specific data.

  • 06

    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.

  • 07

    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.

  • 08

    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.

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