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AI Coding Assistant / Getting Started
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Getting Started with the Telerik UI for .NET MAUI AI Coding Assistant (MCP Server)

Updated on Jun 25, 2026

Use the Telerik UI for .NET MAUI MCP (Model Context Protocol) server to give compatible AI tools grounded context about Telerik UI for .NET MAUI components and APIs. This article shows how to install the server, configure mcp.json, add your Telerik license, verify that the server is running, and start using it in prompts.

The MCP server helps AI-powered IDEs and tools generate more accurate code, answer component questions with Telerik-specific context, and suggest implementations that match Telerik UI for .NET MAUI components.

The Telerik UI for .NET MAUI MCP server works in Chat (Ask) and Agent modes.

Prerequisites

To use the Telerik MAUI MCP server, you need:

Installing the Telerik UI for .NET MAUI MCP Server

Choose the runtime that best matches your development environment:

Install the server package by using one of the following options:

  • By using the dnx script or the dotnet CLI:

    bash
    dnx Telerik.MAUI.MCP

  • By using npm:

    bash
    npm i @progress/telerik-maui-mcp

After the package is available, configure mcp.json, add your Telerik license if needed, restart your MCP client, and then verify that the server is running.

Configuring mcp.json

Use the following values in the mcp.json file of your editor. The exact wrapper differs by client, but the command, args, and server name stay the same.

Setting Name.NET 10 Value.NET 9 ValueNode.js Value
Package Name"Telerik.MAUI.MCP""Telerik.MAUI.MCP""@progress/telerik-maui-mcp"
Type"stdio""stdio""stdio"
Command"dnx""dotnet""npx"
Arguments"Telerik.MAUI.MCP", "--yes""tool", "run", "telerik-maui-assistant""-y"
Server Name"telerik-maui-assistant""telerik-maui-assistant""telerik-maui-assistant"

Configuring Your License

An active Telerik UI for .NET MAUI license is required to use the Telerik MAUI MCP server.

  • When you use the .NET tooling (dnx or dotnet tool install) and the license key file is stored in the default location, the server loads it automatically. The default path is %AppData%\Telerik\telerik-license.txt on Windows and ~/.telerik/telerik-license.txt on Linux.

  • When you use the .NET tooling and the license key file is stored in a different location, add one of the following env settings to mcp.json.

  • When you use Node.js, add one of the following env settings to mcp.json:

    • As a license file path (recommended):

      json
      "env": {
    "TELERIK_LICENSE_PATH": "THE_PATH_TO_YOUR_LICENSE_FILE"
}

    • As a license key value:

      json
      "env": {
    "TELERIK_LICENSE": "YOUR_LICENSE_KEY_HERE"
}

Use a license file path unless you need to share settings across systems. When your Telerik license changes, update the license key before you restart the MCP client.

Client configuration examples in the next section use TELERIK_LICENSE_PATH. If you prefer to pass the license value directly, replace it with TELERIK_LICENSE in the env object.

MCP Clients Configuration

Use the following client-specific examples to create a working mcp.json file. The configuration values are the same across clients, but the config file location and top-level property name differ.

Visual StudioVisual Studio CodeCursor

Early Visual Studio 17.14 versions require the Copilot Chat window to stay open while the solution loads. For platform-specific details, see Use MCP servers in Visual Studio.

  1. Add an .mcp.json file to either of the following locations:

    • For a workspace-specific setup, add the file to the solution folder.
    • For a global setup, add the file to your user directory, %USERPROFILE% (for example, C:\Users\YourName\.mcp.json).
    json
    {
  "servers": {
    "telerik-maui-assistant": {
      "type": "stdio",
      "command": "dnx",
      "args": ["Telerik.MAUI.MCP", "--yes"]
    }
  }
}
    json
    {
  "servers": {
    "telerik-maui-assistant": {
      "type": "stdio",
      "command": "dotnet",
      "args": ["tool", "run", "telerik-maui-assistant"]
    }
  }
}
    json
    {
  "servers": {
    "telerik-maui-assistant": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@progress/telerik-maui-mcp@latest"],
      "env": {
        "TELERIK_LICENSE_PATH": "THE_PATH_TO_YOUR_LICENSE_FILE",
                // or
        "TELERIK_LICENSE": "YOUR_LICENSE_KEY"
      }
    }
  }
}

  2. Restart Visual Studio.

  3. Enable the Telerik MAUI MCP server in the Copilot Chat window's tool selection dropdown.

Visual Studio Code 1.102.1 or later is required. For platform-specific details, see Use MCP servers in Visual Studio Code.

The basic setup in Visual Studio Code involves the following steps:

  1. Enable chat.mcp.enabled in the Visual Studio Code settings.

  2. Create a .vscode/mcp.json file in your workspace root (or user folder for global setup):

    json
    {
  "servers": {
    "telerik-maui-assistant": {
      "type": "stdio",
      "command": "dnx",
      "args": ["Telerik.MAUI.MCP", "--yes"]
    }
  }
}

  3. For global discovery, enable chat.mcp.discovery.enabled in settings.json:

    json
    {
  "chat.mcp.discovery.enabled": true
}

  4. Restart Visual Studio Code.

For Cursor-specific details, see Model Context Protocol in Cursor.

Create a .cursor/mcp.json file in your workspace root (or user folder for global setup):

json
{
  "mcpServers": {
    "telerik-maui-assistant": {
      "type": "stdio",
      "command": "dnx",
      "args": ["Telerik.MAUI.MCP", "--yes"]
    }
  }
}
json
{
  "mcpServers": {
    "telerik-maui-assistant": {
      "type": "stdio",
      "command": "dotnet",
      "args": ["tool", "run", "telerik-maui-assistant"]
    }
  }
}
json
{
  "mcpServers": {
    "telerik-maui-assistant": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@progress/telerik-maui-mcp@latest"],
      "env": {
        "TELERIK_LICENSE_PATH": "THE_PATH_TO_YOUR_LICENSE_FILE",
                // or
        "TELERIK_LICENSE": "YOUR_LICENSE_KEY"
      }
    }
  }
}

Verifying That the MCP Server Is Working

After you restart the client, confirm that the server is available before you begin a larger prompt:

  1. Start a new chat or agent session.
  2. Begin the prompt with one of the Telerik triggers.
  3. Approve tool permissions when the client asks.
  4. Confirm that the editor shows the Telerik MAUI MCP server as running.

Use one of the following trigger strings in your prompt:

  • #telerik
  • #telerikmaui
  • #telerik-maui-assistant

Look for one of the following client messages:

  • Visual Studio: Running telerik-maui-assistant
  • Visual Studio Code: Running telerik-maui-assistant
  • Cursor: Calling MCP tool telerik-maui-assistant

Troubleshooting

If the server does not appear or does not respond, check the following items first:

  • Confirm that your installed runtime matches the configuration in mcp.json.
  • Confirm that the JSON file is valid and uses the correct top-level property for your client.
  • Confirm that your Telerik license file path or license value is available to the editor process.
  • Restart the editor after every mcp.json change.

Known Issue: Hanging tool calls in Visual Studio

When you use Telerik AI tools in Visual Studio, GitHub Copilot may:

  • hang during tool invocation;
  • show UI for a successful tool response, but actually fail silently;
  • continue generation without waiting for parallel tool calls.

In these cases, the response may be generated but not shown in the Copilot Agent UI.

This is a known issue in Visual Studio Copilot, not in Telerik MCP servers or Telerik AI tools, and it does not reproduce in Visual Studio Code.

For more details, see the Visual Studio Developer Community issue for hanging Copilot tool calls.

Microsoft has marked the issue as Fixed - Pending Release. A future Visual Studio update is expected to resolve it.

Usage

MCP clients do not always call tools deterministically. When your client supports explicit tool selection, reference the Telerik server directly in the prompt to increase the chance that the client uses Telerik-specific context.

Use the following practices when you work with the Telerik MAUI MCP server:

  1. Start the prompt with #telerik, #telerikmaui, or #telerik-maui-assistant.
  2. Keep the request specific by naming the Telerik control, layout, data source, or behavior you want.
  3. Grant permissions when the client prompts you.
  4. Start a fresh session for unrelated prompts so earlier context does not affect the next result.
  5. Use the server in Chat (Ask) and Agent modes.

Increasing Tool Selection Reliability

To increase the likelihood that your AI client uses the Telerik server, add client-specific instructions that mention Telerik UI for .NET MAUI as a preferred source for component generation and API guidance:

Sample Prompts

Use prompts like the following examples when you want the client to generate Telerik-specific code:

  • "#telerik-maui-assistant Create new maui project with Telerik. Add sample usage of the DataGrid component."
  • "#telerik-maui-assistant Create a DataGrid with 3 columns - Name, Country, City. Add the corresponding business object in the code behind and populate it with sample data. Add 20 entries to the data."
  • "#telerik-maui-assistant Add CollectionView. Enable drag and drop operation in the control."

Number of Requests

A Telerik Subscription license is required in order to use the Telerik MAUI AI Coding Assistant. Trial users can make a limited number of requests per year.

Local AI Model Integration

You can use the Telerik MAUI MCP server with a local large language model (LLM) instead of a cloud-hosted model:

  1. Run a local model, for example, Ollama.
  2. Use a bridge package like MCP-LLM Bridge.
  3. Connect the local model and the Telerik MAUI MCP server through the bridge.

This setup allows you to use the Telerik AI Coding Assistant without a cloud-based AI model.

See Also

In this article
PrerequisitesInstalling the Telerik UI for .NET MAUI MCP ServerConfiguring mcp.jsonConfiguring Your LicenseMCP Clients ConfigurationVerifying That the MCP Server Is WorkingTroubleshootingUsageIncreasing Tool Selection ReliabilitySample PromptsNumber of RequestsLocal AI Model IntegrationSee Also
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