Compatible with every major AI agent and IDE
What is the Together AI Alternative MCP Server?
Connect Together AI to your AI agent to leverage the world's fastest inference cloud for open-source models. This server provides a comprehensive suite of tools for generative AI, from text and image creation to advanced fine-tuning and batch processing.
What you can do
- Inference & Chat — Generate high-quality responses using models like Llama 3.3, Qwen, and Mixtral via chat or text completions.
- Media Generation — Create stunning images and videos from text prompts using state-of-the-art models like Flux and Stable Diffusion.
- Audio Services — Convert text to speech (TTS) or transcribe audio files (STT) with speaker identification.
- Advanced RAG — Generate vector embeddings and rerank documents to build high-performance search and retrieval systems.
- Model Management — Manage fine-tuning jobs, dedicated endpoints, and file uploads for custom model training.
- Batch Processing — Handle large-scale asynchronous workloads efficiently using the Batch API.
How it works
- Subscribe to this server
- Enter your Together AI API Key
- Start building with the most powerful open-source models directly from your MCP-compatible client
Who is this for?
- AI Developers — integrate cutting-edge LLMs and image models into your applications without managing infrastructure
- Data Scientists — fine-tune models on custom datasets and manage checkpoints seamlessly
- Product Teams — prototype and scale AI features using a unified, high-performance API
Built-in capabilities (27)
Cancel a running batch job
Text-to-Speech (TTS) generation
Transcriptions (STT) from audio file
Create a new asynchronous batch job
3-70B-Instruct-Turbo. Generate a model response for a given chat conversation
Turn text into vector embeddings
Create a dedicated endpoint for predictable performance
Create a fine-tuning job
Generate images from text prompts
Reorder documents by relevance to a query
Generate text completions for a given prompt
Create videos from text or image prompts
Delete a dedicated endpoint
Delete an uploaded file
Delete a fine-tuning job
Get details of a specific batch job
Get details of a specific dedicated endpoint
Retrieve metadata for a specific file
Get details of a specific fine-tuning job
List all batch jobs
List all dedicated endpoints
List all uploaded files
List checkpoints for a fine-tuning job
List all fine-tuning jobs
List all available models on Together AI
Update a dedicated endpoint (Start/Stop/Scale)
Upload a file for fine-tuning, evals, or batch inference
Why Claude Code?
Claude Code registers Together AI Alternative as an MCP server in a single terminal command. Once connected, Claude Code discovers all 27 tools at runtime and can call them headlessly. ideal for CI/CD pipelines, cron jobs, and automated workflows where Together AI Alternative data drives decisions without human intervention.
- —
Single-command setup:
claude mcp addregisters the server instantly. no config files to edit or applications to restart - —
Terminal-native workflow means MCP tools integrate seamlessly into shell scripts, CI/CD pipelines, and automated DevOps tasks
- —
Claude Code runs headlessly, enabling unattended batch processing using Together AI Alternative tools in cron jobs or deployment scripts
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Built by the same team that created the MCP protocol, ensuring first-class compatibility and the fastest adoption of new protocol features
Together AI Alternative in Claude Code
Together AI Alternative and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Together AI Alternative to Claude Code through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Together AI Alternative in Claude Code
The Together AI Alternative MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 27 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Claude Code only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Together AI Alternative for Claude Code
Every tool call from Claude Code to the Together AI Alternative MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
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.
How do I add an MCP server to Claude Code?
Run claude mcp add <name> --transport http "<url>" in your terminal. Claude Code registers the server and discovers all tools immediately.
Can Claude Code run MCP tools in headless mode?
Yes. Claude Code supports non-interactive execution, making it ideal for scripts, cron jobs, and CI/CD pipelines that need MCP tool access.
How do I list all connected MCP servers?
Run claude mcp in your terminal to see all registered servers and their status, or type /mcp inside an active Claude Code session.
Command not found: claude
Ensure Claude Code is installed globally: npm install -g @anthropic-ai/claude-code
Connection timeout
Check your internet connection and verify the Edge URL is reachable
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