How to Use the LocalAI MCP in Cursor

Q: How do I configure LocalAI inside Cursor?

Create a .cursor/mcp.json file in your project root or add the configuration globally. Define the MCP Server with its node startup command, and Cursor will automatically spin up the connection whenever you open the workspace.

Q: Can I generate placeholder assets using LocalAI in Cursor?

Yes. You can ask the Cursor agent to run generateimage to create mockups or UI icons directly on your local machine, saving them straight to your project directory.

Q: What should I do if LocalAI tools time out in Cursor?

Heavy tasks like transcribeaudio can time out if your local hardware is overloaded. Check your system load with getsysteminfo and make sure your local models are properly quantized to fit your VRAM.

Q: Does this integration support custom model templates?

Yes. The server uses applymodel to install pre-configured templates from the gallery, which your editor can immediately use for specialized coding tasks.

Inject local code completions, embeddings, and image generation directly into your Cursor agent workflows.

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Connect LocalAI MCP to Cursor

Create your Vinkius account to connect LocalAI 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 LocalAI with Cursor

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Rerank code documents locally within Cursor

Running `rerank_documents` allows your Cursor agent to sort through your local files based on semantic relevance to your active coding task. This MCP Server keeps your data local and eliminates the need to rely on cloud services to search through your codebase in Cursor. Your proprietary codebase stays private while still letting your editor quickly find relevant code snippets. You can generate high-dimensional vectors on your own hardware using `create_embeddings` without sending sensitive code to third parties.

Execute local completions in the Cursor editor

The `chat_completions` and `open_responses` tools generate code blocks and explain bugs using whatever open-source models are active on your machine. You write code in the editor without worrying about API limits or privacy leaks. If you need to test different models for specific coding tasks, use `list_models` to see what is available. This lets you quickly switch between lightweight coding models and larger reasoning models depending on the complexity of your file.

Analyze UI mockups and detect objects in Cursor

The `detect_objects` tool lets your Cursor agent check UI screenshots to verify layout positioning without uploading files to cloud providers. Connecting this MCP tool gives you instant visual debugging directly from your editor. For applications dealing with biometric features, you can test face recognition pipelines locally. The tools `face_verify` and `face_identify` let your agent write and test authentication code against local image stores in real time.

Setup guide

Set up LocalAI 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 LocalAI 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 LocalAI transactions." If the MCP tools are loaded correctly, Cursor will call the LocalAI tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by LocalAI. 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 LocalAI MCP in Cursor

Create a `.cursor/mcp.json` file in your project root or add the configuration globally. Define the MCP Server with its node startup command, and Cursor will automatically spin up the connection whenever you open the workspace.

Yes. You can ask the Cursor agent to run `generate_image` to create mockups or UI icons directly on your local machine, saving them straight to your project directory.

Heavy tasks like `transcribe_audio` can time out if your local hardware is overloaded. Check your system load with `get_system_info` and make sure your local models are properly quantized to fit your VRAM.

Yes. The server uses `apply_model` to install pre-configured templates from the gallery, which your editor can immediately use for specialized coding tasks.

Your source code and database schemas are processed entirely on your local hardware. The MCP server runs inside an isolated sandbox and communicates over local ports, ensuring your IP never touches external networks.

Use it with your favorite AI tools

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

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