How to Use the Together AI MCP in Cursor

Q: Can I use this MCP Server for image generation with Together AI?

Absolutely. The generateimage tool takes descriptive prompts and generates images, which can then be used in documentation or UI mockups directly from your code context.

Q: Is setup complicated when using Together AI with Cursor?

No. You just need to add the server details under mcpServers in your project's .cursor/mcp.json file, or you can use one-click install links from the documentation.

Q: How do I manage different types of models using Together AI and Cursor?

You check listavailablemodels. This tool ensures that when your agent is writing code, it knows exactly which model IDs are valid for both text completion and chat operations.

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Connect Together AI MCP to Cursor

Create your Vinkius account to connect Together AI to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Together AI with Cursor

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Inject real data into your code editor.

The `generate_embeddings` tool takes model IDs and a list of strings, spitting out vector embeddings. You can use this live context right in your file because the AI calls the API response directly into your writing session. This means you aren't working with mock data or stubs; the code actually uses real-world context derived from the MCP Server.

Run chat completions for coding help.

The `chat_completion` tool lets your agent manage conversations while keeping track of system prompts and messages. You can pass a model ID and an array of messages to guide complex, multi-step code generation. This keeps the entire context visible to you as the developer, making it easier to debug or adjust the AI's output on the fly.

List all available AI models in one place.

Need to switch up the LLM for a specific task? The `list_available_models` tool pulls every Together AI model ID into your project scope. It’s a quick check that prevents you from using an outdated or restricted version. This gives you immediate visibility over all options before committing to a text completion or code generation step.

Setup guide

Set up Together AI MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the Together AI MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent Together AI transactions." If the MCP tools are loaded correctly, Cursor will call the Together AI tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "together-ai-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Together AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Together AI MCP in Cursor

Cursor runs the MCP Server tools right within your editor's agent mode. When the AI needs live context, it calls the tool, gets a real API response, and inserts that data directly into the code you're writing.

Absolutely. The `generate_image` tool takes descriptive prompts and generates images, which can then be used in documentation or UI mockups directly from your code context.

It handles text inputs (strings) and message history arrays. This is the core data type needed to create embeddings, write completions, or generate structured chat results.

No. You just need to add the server details under `mcpServers` in your project's `.cursor/mcp.json` file, or you can use one-click install links from the documentation.

You check `list_available_models`. This tool ensures that when your agent is writing code, it knows exactly which model IDs are valid for both text completion and chat operations.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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