diff --git a/README.md b/README.md
index 389deac..1630a95 100644
--- a/README.md
+++ b/README.md
@@ -4,6 +4,9 @@ The official Node.js SDK for [Maxun](https://maxun.dev) - turn any website into
 
 Works with both Maxun Cloud and Maxun Open Source - automatically handles the differences for you.
 
+https://github.com/user-attachments/assets/71a6f10b-5b2a-45dd-9ef7-53d0bcf2b76d
+
+
 ## What can you do with Maxun SDK?
 
 - **Extract structured data** from any website
diff --git a/examples/llm-extraction.ts b/examples/llm-extraction.ts
index 7314402..f639512 100644
--- a/examples/llm-extraction.ts
+++ b/examples/llm-extraction.ts
@@ -6,6 +6,7 @@
  * - LLM automatically generates the extraction workflow
  * - Support for multiple LLM providers (Ollama, Anthropic, OpenAI)
  * - Creates a reusable robot that can be executed anytime
+ * - Auto-search: When no URL is provided, the system searches for the website automatically
  *
  * Site: Y Combinator Companies (https://www.ycombinator.com/companies)
  */
@@ -20,34 +21,51 @@ async function main() {
   });
 
   try {
-    console.log('Creating robot using LLM extraction...\n');
-
-    // Use natural language to describe what to extract
-    // The LLM will automatically generate the workflow
-    const robot = await extractor.extract(
-      'https://www.ycombinator.com/companies',
-      {
-        prompt: 'Extract the first 15 YC company names, their descriptions, and batch information',
-        llmProvider: 'ollama', // or 'anthropic', 'openai'
-        llmModel: 'llama3.2-vision', // default for ollama
-        llmBaseUrl: 'http://localhost:11434', // ollama default
-        robotName: 'YC Companies LLM Extractor'
-      }
-    );
-
-    console.log(`✓ Robot created: ${robot.id}`);
+    console.log('Example 1: Creating robot with configured URL...\n');
+
+    const robot = await extractor.extract({
+      url: 'https://www.ycombinator.com/companies',
+      prompt: 'Extract the first 15 YC company names, their descriptions, and batch information',
+      llmProvider: 'ollama',
+      llmModel: 'llama3.2-vision',
+      llmBaseUrl: 'http://localhost:11434',
+      robotName: 'YC Companies LLM Extractor'
+    });
+
+    console.log(`Robot created: ${robot.id}`);
 
     // Execute the generated robot
     console.log('Executing robot...\n');
     const result = await robot.run();
 
-    console.log(`✓ Extraction completed!`);
+    console.log(`Extraction completed!`);
     console.log(`  Status: ${result.status}`);
     console.log(`  Companies extracted: ${result.data.listData?.length || 0}\n`);
 
     console.log('First 3 companies:');
     console.log(JSON.stringify(result.data.listData?.slice(0, 3), null, 2));
 
+    console.log('\n\nExample 2: Creating robot without configured URL...\n');
+
+    const autoSearchRobot = await extractor.extract({
+      prompt: 'Extract company names and descriptions from the YCombinator Companies page',
+      llmProvider: 'ollama',
+      robotName: 'YC Auto-Search Extractor'
+    });
+
+    console.log(`Auto-search robot created: ${autoSearchRobot.id}`);
+
+    // Execute the generated robot
+    console.log('Executing robot...\n');
+    const autoSearchResult = await autoSearchRobot.run();
+
+    console.log(`Extraction completed!`);
+    console.log(`  Status: ${autoSearchResult.status}`);
+    console.log(`  Companies extracted: ${autoSearchResult.data.listData?.length || 0}\n`);
+
+    console.log('First 3 companies:');
+    console.log(JSON.stringify(autoSearchResult.data.listData?.slice(0, 3), null, 2));
+
     // Note: For Anthropic (recommended for best results):
     // llmProvider: 'anthropic',
     // llmModel: 'claude-3-5-sonnet-20241022',
@@ -73,3 +91,4 @@ if (!process.env.MAXUN_API_KEY) {
 }
 
 main();
+
diff --git a/src/client/maxun-client.ts b/src/client/maxun-client.ts
index 4fc6709..0933c03 100644
--- a/src/client/maxun-client.ts
+++ b/src/client/maxun-client.ts
@@ -238,8 +238,10 @@ export class Client {
 
   /**
    * LLM-based extraction - extract data using natural language prompt
+   * URL is optional - if not provided, the server will search for the target website based on the prompt
    */
-  async extractWithLLM(url: string, options: {
+  async extractWithLLM(options: {
+    url?: string;
     prompt: string;
     llmProvider?: 'anthropic' | 'openai' | 'ollama';
     llmModel?: string;
@@ -250,7 +252,7 @@ export class Client {
     const response = await this.axios.post<ApiResponse<any>>(
       '/extract/llm',
       {
-        url,
+        url: options.url || undefined,
         prompt: options.prompt,
         llmProvider: options.llmProvider,
         llmModel: options.llmModel,
diff --git a/src/extract.ts b/src/extract.ts
index 8408822..abe893f 100644
--- a/src/extract.ts
+++ b/src/extract.ts
@@ -75,8 +75,8 @@ export class Extract {
    * LLM-based extraction - create a robot using natural language prompt
    * The robot is saved and can be executed anytime by the user
    *
-   * @param url - The URL to extract data from
    * @param options - Extraction options
+   * @param options.url - (Optional) The URL to extract data from. If not provided, the system will automatically search for the target website based on the prompt.
    * @param options.prompt - Natural language prompt describing what to extract
    * @param options.llmProvider - LLM provider to use: 'anthropic', 'openai', or 'ollama' (default: 'ollama')
    * @param options.llmModel - Model name (default: 'llama3.2-vision' for ollama, 'claude-3-5-sonnet-20241022' for anthropic, 'gpt-4-vision-preview' for openai)
@@ -85,7 +85,8 @@ export class Extract {
    * @param options.robotName - Optional custom name for the robot
    * @returns Robot instance that can be executed
    */
-  async extract(url: string, options: {
+  async extract(options: {
+    url?: string;
     prompt: string;
     llmProvider?: 'anthropic' | 'openai' | 'ollama';
     llmModel?: string;
@@ -93,7 +94,7 @@ export class Extract {
     llmBaseUrl?: string;
     robotName?: string;
   }): Promise<Robot> {
-    const robotData = await this.client.extractWithLLM(url, options);
+    const robotData = await this.client.extractWithLLM(options);
     const robot = await this.client.getRobot(robotData.robotId);
     return new Robot(this.client, robot);
   }