diff --git a/src/praisonai-ts/examples/README-tool-examples.md b/src/praisonai-ts/examples/README-tool-examples.md
index cc2967b2b..180c26fa4 100644
--- a/src/praisonai-ts/examples/README-tool-examples.md
+++ b/src/praisonai-ts/examples/README-tool-examples.md
@@ -191,3 +191,17 @@ const agent = new Agent({
 // Start the agent with a prompt that will trigger tool usage
 agent.start("What's the weather in Paris, the time in Tokyo, and what is 25 * 4?");
 ```
+
+## MCP SSE Tool Integration
+
+PraisonAI can use remote tools exposed via the Model Context Protocol over Server-Sent Events.
+
+1. Start the Python SSE server in another terminal:
+```bash
+python ../../praisonai-agents/tests/mcp-sse-direct-server.py --host 127.0.0.1 --port 8080
+```
+
+2. Run the TypeScript example which connects to this server:
+```bash
+npx ts-node examples/tools/mcp-sse.ts
+```
diff --git a/src/praisonai-ts/examples/tools/mcp-sse.ts b/src/praisonai-ts/examples/tools/mcp-sse.ts
new file mode 100644
index 000000000..0c6293282
--- /dev/null
+++ b/src/praisonai-ts/examples/tools/mcp-sse.ts
@@ -0,0 +1,70 @@
+import { Agent } from '../../src/agent';
+import { MCP } from '../../src/tools/mcpSse';
+
+async function main() {
+  // Connect to the running SSE server
+  const mcp = new MCP('http://127.0.0.1:8080/sse');
+  try {
+    await mcp.initialize();
+  } catch (error) {
+    console.error('Failed to connect to MCP SSE server:', error);
+    console.error('Please ensure the server is running at http://127.0.0.1:8080/sse');
+    process.exit(1);
+  }
+
+  // Create tool functions that call the remote MCP tools
+  const toolFunctions: Record<string, (...args: any[]) => Promise<any>> = {};
+  
+  if (mcp.tools.length === 0) {
+    console.warn('Warning: No MCP tools available. Make sure the MCP server is running.');
+  }
+  
+  for (const tool of mcp) {
+    if (!tool || typeof tool.name !== 'string') {
+      console.warn('Skipping invalid tool:', tool);
+      continue;
+    }
+    
+    const paramNames = Object.keys(tool.schemaProperties || {});
+    toolFunctions[tool.name] = async (...args: any[]) => {
+      const params: Record<string, any> = {};
+      
+      if (args.length === 1 && typeof args[0] === 'object' && args[0] !== null) {
+        // If single object argument, use it directly as params
+        Object.assign(params, args[0]);
+      } else {
+        // Map positional arguments with validation
+        if (args.length > paramNames.length) {
+          console.warn(
+            `Tool ${tool.name}: Too many arguments provided. Expected ${paramNames.length}, got ${args.length}`
+          );
+        }
+        for (let i = 0; i < Math.min(args.length, paramNames.length); i++) {
+          params[paramNames[i]] = args[i];
+        }
+      }
+      return tool.execute(params);
+    };
+  }
+
+  const agent = new Agent({
+    instructions: 'Use the tools to greet people and report the weather.',
+    name: 'MCPAgent',
+    tools: mcp.toOpenAITools(),
+    toolFunctions
+  });
+
+  try {
+    const result = await agent.start('Say hello to John and tell the weather in London.');
+    console.log('\nFinal Result:', result);
+  } catch (error) {
+    console.error('Agent execution failed:', error);
+  } finally {
+    // Clean up MCP connection
+    await mcp.close();
+  }
+}
+
+if (require.main === module) {
+  main();
+}
diff --git a/src/praisonai-ts/package.json b/src/praisonai-ts/package.json
index bd8f49b25..30d3bdc1f 100644
--- a/src/praisonai-ts/package.json
+++ b/src/praisonai-ts/package.json
@@ -62,7 +62,8 @@
     "fast-xml-parser": "^4.5.1",
     "node-fetch": "^2.6.9",
     "openai": "^4.81.0",
-    "praisonai": "^1.0.19"
+    "praisonai": "^1.0.19",
+    "@modelcontextprotocol/sdk": "^1.12.1"
   },
   "optionalDependencies": {
     "boxen": "^7.1.1",
diff --git a/src/praisonai-ts/src/tools/index.ts b/src/praisonai-ts/src/tools/index.ts
index 283b0e4be..f57b493e8 100644
--- a/src/praisonai-ts/src/tools/index.ts
+++ b/src/praisonai-ts/src/tools/index.ts
@@ -20,4 +20,5 @@ export class BaseTool implements Tool {
 }
 
 // Export all tool modules
-export * from './arxivTools';
\ No newline at end of file
+export * from './arxivTools';
+export * from './mcpSse';
diff --git a/src/praisonai-ts/src/tools/mcpSse.ts b/src/praisonai-ts/src/tools/mcpSse.ts
new file mode 100644
index 000000000..46683a3da
--- /dev/null
+++ b/src/praisonai-ts/src/tools/mcpSse.ts
@@ -0,0 +1,116 @@
+import { Client } from '@modelcontextprotocol/sdk/client/index.js';
+import { SSEClientTransport } from '@modelcontextprotocol/sdk/client/sse.js';
+import { BaseTool } from './index';
+
+export interface MCPToolInfo {
+  name: string;
+  description?: string;
+  inputSchema?: any;
+}
+
+export class MCPTool extends BaseTool {
+  private client: Client;
+  private inputSchema: any;
+
+  constructor(info: MCPToolInfo, client: Client) {
+    super(info.name, info.description || `Call the ${info.name} tool`);
+    this.client = client;
+    this.inputSchema = info.inputSchema || { type: 'object', properties: {}, required: [] };
+  }
+
+  get schemaProperties(): Record<string, any> | undefined {
+    return this.inputSchema?.properties;
+  }
+
+  async execute(args: any = {}): Promise<any> {
+    try {
+      const result: any = await this.client.callTool({ name: this.name, arguments: args });
+      if (result.structuredContent) {
+        return result.structuredContent;
+      }
+      if (Array.isArray(result.content) && result.content.length > 0) {
+        const item = result.content[0];
+        if (typeof item.text === 'string') return item.text;
+      }
+      return result;
+    } catch (error) {
+      throw new Error(`Failed to execute tool ${this.name}: ${error instanceof Error ? error.message : String(error)}`);
+    }
+  }
+
+  toOpenAITool() {
+    return {
+      type: 'function',
+      function: {
+        name: this.name,
+        description: this.description,
+        parameters: this.inputSchema
+      }
+    };
+  }
+}
+
+export class MCP implements Iterable<MCPTool> {
+  tools: MCPTool[] = [];
+  private client: Client | null = null;
+
+  constructor(private url: string, private debug = false) {
+    if (debug) {
+      console.log(`MCP client initialized for URL: ${url}`);
+    }
+  }
+
+  async initialize(): Promise<void> {
+    if (this.client) {
+      if (this.debug) console.log('MCP client already initialized');
+      return;
+    }
+    
+    try {
+      this.client = new Client({ name: 'praisonai-ts-mcp', version: '1.0.0' });
+      const transport = new SSEClientTransport(new URL(this.url));
+      await this.client.connect(transport);
+      const { tools } = await this.client.listTools();
+      this.tools = tools.map((t: any) => new MCPTool({
+        name: t.name,
+        description: t.description,
+        inputSchema: t.inputSchema
+      }, this.client as Client));
+      
+      if (this.debug) console.log(`Initialized MCP with ${this.tools.length} tools`);
+    } catch (error) {
+      if (this.client) {
+        await this.client.close().catch(() => {});
+        this.client = null;
+      }
+      throw new Error(`Failed to initialize MCP client: ${error instanceof Error ? error.message : 'Unknown error'}`);
+    }
+  }
+
+  [Symbol.iterator](): Iterator<MCPTool> {
+    return this.tools[Symbol.iterator]();
+  }
+
+  toOpenAITools() {
+    return this.tools.map(t => t.toOpenAITool());
+  }
+
+  async close(): Promise<void> {
+    if (this.client) {
+      try {
+        await this.client.close();
+      } catch (error) {
+        if (this.debug) {
+          console.warn('Error closing MCP client:', error);
+        }
+      } finally {
+        this.client = null;
+        this.tools = [];
+      }
+    }
+  }
+
+  get isConnected(): boolean {
+    return this.client !== null;
+  }
+}