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‎ai/copilot-extension.md‎

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@@ -13,10 +13,10 @@ The Telerik MAUI [GitHub Copilot](https://github.com/features/copilot) extension
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This extension enhances GitHub Copilot with proprietary context about Telerik MAUI controls, helping you:
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* Generate code snippets using Telerik MAUI components
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* Get contextual suggestions for component properties and methods
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* Access best practices and implementation patterns
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* Speed up development with AI-powered code completion
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* Generate code snippets using Telerik MAUI components.
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* Get contextual suggestions for component properties and methods.
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* Access best practices and implementation patterns.
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* Speed up development with AI-powered code completion.
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## Prerequisites
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If you encounter issues:
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* Ensure the `@telerikmaui` mention is properly highlighted in your prompt
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* Verify that you have an active GitHub Copilot subscription
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* Restart your IDE after installation
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* Check that you're in Chat mode, not Edit or Agent mode
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* Ensure the `@telerikmaui` mention is properly highlighted in your prompt.
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* Verify that you have an active GitHub Copilot subscription.
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* Restart your IDE after installation.
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* Check that you're in Chat mode, not Edit or Agent mode.
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## See Also
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‎ai/mcp-server.md‎

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To use the Telerik MAUI MCP server, you need:
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* [Node.js](https://nodejs.org/en) 18 or newer
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* An [MCP-compatible client](https://modelcontextprotocol.io/clients) that supports **MCP tools** (latest version recommended)
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* [Node.js](https://nodejs.org/en) 18 or newer.
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* An [MCP-compatible client](https://modelcontextprotocol.io/clients) that supports **MCP tools** (latest version recommended).
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@[template](/_contentTemplates/common/ai-coding-assistant.md#getting-started)
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Add your [Telerik license key]({%slug set-up-your-license%}) as an environment parameter in your `mcp.json` file using one of these options:
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**Option 1: License File Path (Recommended)**
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```json
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"env": {
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"TELERIK_LICENSE_PATH": "THE_PATH_TO_YOUR_LICENSE_FIL"
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}
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```
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Option 1: License File Path (Recommended)
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**Option 2: Direct License Key**
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```json
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"env": {
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"TELERIK_LICENSE": "YOUR_LICENSE_KEY_HERE"
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}
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```
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```json
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"env": {
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"TELERIK_LICENSE_PATH": "THE_PATH_TO_YOUR_LICENSE_FIL"
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}
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```
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Option 2: Direct License Key
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```json
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"env": {
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"TELERIK_LICENSE": "YOUR_LICENSE_KEY_HERE"
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}
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```
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> Option 1 is recommended unless you're sharing settings across different systems. Remember to [update your license key]({%slug set-up-your-license%}#updating-your-license-key) when necessary.
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> Early Visual Studio 17.14 versions require the Copilot Chat window to be open when opening a solution for the MCP server to work properly.
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**Workspace-Specific Setup:**
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### Workspace-Specific Setup:
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1. Add `.mcp.json` to your solution folder:
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```json
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{
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"servers": {
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"telerikMauiAssistant": {
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"type": "stdio",
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"command": "npx",
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"args": ["-y", "@progress/telerik-maui-mcp@latest"],
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"env": {
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"TELERIK_LICENSE_PATH": "THE_PATH_TO_YOUR_LICENSE_FILE",
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// or
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"TELERIK_LICENSE": "YOUR_LICENSE_KEY"
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}
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}
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}
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}
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```
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```json
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{
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"servers": {
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"telerikMauiAssistant": {
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"type": "stdio",
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"command": "npx",
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"args": ["-y", "@progress/telerik-maui-mcp@latest"],
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"env": {
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"TELERIK_LICENSE_PATH": "THE_PATH_TO_YOUR_LICENSE_FILE",
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// or
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"TELERIK_LICENSE": "YOUR_LICENSE_KEY"
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}
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}
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}
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}
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```
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2. Restart Visual Studio.
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3. Enable the `telerikMauiAssistant` tool in the [Copilot Chat window's tool selection dropdown](https://learn.microsoft.com/en-us/visualstudio/ide/mcp-servers?view=vs-2022#configuration-example-with-github-mcp-server).
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**Global Setup:**
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### Global Setup:
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Add the `.mcp.json` file to your user directory (`%USERPROFILE%`, e.g., `C:\Users\YourName\.mcp.json`).
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### Visual Studio Code
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## Visual Studio Code
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For complete setup instructions, see [Use MCP servers in Visual Studio Code](https://code.visualstudio.com/docs/copilot/chat/mcp-servers).
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> Visual Studio Code 1.102.1 or newer is required to use the Telerik MCP Server
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**Setup Steps:**
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The basic setup in Visual Studio Code follows these steps:
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1. Enable [`chat.mcp.enabled`](vscode://settings/chat.mcp.enabled) in Visual Studio Code settings.
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2. Create `.vscode/mcp.json` in your workspace root (or user folder for global setup):
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```json
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{
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"servers": {
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"telerik-maui-assistant": {
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"type": "stdio",
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"command": "npx",
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"args": ["-y", "@progress/telerik-maui-mcp@latest"],
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"env": {
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"TELERIK_LICENSE_PATH": "THE_PATH_TO_YOUR_LICENSE_FILE",
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// or
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"TELERIK_LICENSE": "YOUR_LICENSE_KEY"
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}
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}
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}
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}
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```
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```json
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{
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"servers": {
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"telerik-maui-assistant": {
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"type": "stdio",
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"command": "npx",
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"args": ["-y", "@progress/telerik-maui-mcp@latest"],
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"env": {
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"TELERIK_LICENSE_PATH": "THE_PATH_TO_YOUR_LICENSE_FILE",
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// or
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"TELERIK_LICENSE": "YOUR_LICENSE_KEY"
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}
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}
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}
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}
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```
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3. For global discovery, enable [`chat.mcp.discovery.enabled`](vscode://settings/chat.mcp.discovery.enabled) in `settings.json`:
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```json
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{
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"chat.mcp.discovery.enabled": true
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}
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```
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```json
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{
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"chat.mcp.discovery.enabled": true
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}
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```
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4. Restart Visual Studio Code.
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### Cursor
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## Cursor
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For complete setup instructions, see [Model Context Protocol](https://docs.cursor.com/context/mcp).
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### Sample Prompts
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The following examples demonstrate useful prompts for the Telerik .NET MAUI MCP Server:
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"`/telerik` Generate a DataGrid with sorting and paging. Bind it to a Person model with sample ViewModel."
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You can use the Telerik MAUI MCP server with local large language models (LLMs):
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1. Run a local model through [Ollama](https://ollama.com).
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1. Run a local model, for example, through [Ollama](https://ollama.com).
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2. Use a bridge package like [MCP-LLM Bridge](https://github.com/patruff/ollama-mcp-bridge).
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3. Connect your local model to the Telerik MCP server.
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‎ai/overview.md‎

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### Key Differences
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**MCP Server:**
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* More powerful and handles complex, multi-step prompts
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* Works with MCP-enabled clients like Cursor or GitHub Copilot in Agent mode
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* Can directly suggest changes and rebuild applications to verify generated code
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* Responses are primarily code-focused
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**GitHub Copilot Extension:**
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* Provides detailed explanations alongside code suggestions
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* Offers shorter, focused code snippets
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* Better for learning and understanding implementation approaches
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| Feature | MCP Server | GitHub Copilot Extension |
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|------------------------|---------------------------------------------------------------------------|------------------------------------------------------------|
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| Prompt Handling | Handles complex, multi-step prompts | Offers shorter, focused code snippets |
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| Client Compatibility | Works with MCP-enabled clients (e.g., Cursor, Copilot Agent mode) | Integrated as a Copilot extension |
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| Code Suggestions | Can directly suggest changes and rebuild applications to verify code | Provides detailed explanations alongside code suggestions |
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| Response Focus | Primarily code-focused | Better for learning and understanding implementation |
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## Getting Started
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| License Type | Request Limit |
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|--------------|---------------|
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| **Perpetual** | 50 requests per year |
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| **Subscription** | Virtually unlimited with fair use threshold of 300 requests per day |
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| **Trial** | 300 requests per trial period (does not reset with new trial activations) |
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| Perpetual | 50 requests per year |
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| Subscription | Virtually unlimited with fair use threshold of 300 requests per day |
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| Trial | 300 requests per trial period (does not reset with new trial activations) |
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> **Important:** All Telerik AI tools share a single request quota for your Telerik account. Usage from the [Telerik Copilot extension]({%slug ai-copilot-extension%}) and [Telerik MCP server]({%slug ai-mcp-server%}) counts toward the same limit. Complex prompts in the MCP server may consume multiple requests.
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> All Telerik AI tools share a single request quota for your Telerik account. Usage from the [Telerik Copilot extension]({%slug ai-copilot-extension%}) and [Telerik MCP server]({%slug ai-mcp-server%}) counts toward the same limit. Complex prompts in the MCP server may consume multiple requests.
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## Privacy
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The Telerik MAUI AI Coding Assistant operates under strict privacy guidelines:
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**Data Access:**
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Data Access:
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* No access to your workspace and application code.
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* Exception: when using the Telerik MCP server (or any other MCP server), the LLM generates parameters for the MCP server request, which may include parts of your application code.
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**Data Usage:**
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Data Usage:
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* Your prompts are not used to train Telerik AI models.
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* Does not generate or access AI responses.
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* Provides enhanced context to improve responses from your chosen AI model (GPT, Gemini, Claude, etc.).
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**Data Storage:**
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Data Storage:
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* Prompts and context are anonymized and stored only for statistical analysis and troubleshooting.
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* No association between prompts and your Telerik user account.
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* Usage metrics are collected to ensure [license compliance](#number-of-requests).
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> Review the terms and privacy policies of your selected AI model and AI client.
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> Make sure also to review the terms and privacy policies of your selected AI model and AI client.
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## Next Steps
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