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+# Basic Agent Setup with MCP
+
+## Overview
+
+This document shows how to set up a basic Swarms agent with MCP (Model Context Protocol) integration for client-side operations.
+
+## Basic Agent Setup
+
+```python
+from swarms import Agent
+from swarms.tools.mcp_integration import MCPServerSseParams
+
+# Configure MCP server parameters
+mcp_params = MCPServerSseParams(
+    url="http://localhost:8081/sse",  # MCP server SSE endpoint
+    headers={"Accept": "text/event-stream"},  # Required for SSE
+    timeout=5.0  # Connection timeout in seconds
+)
+
+# Initialize agent with MCP configuration
+agent = Agent(
+    agent_name="basic_agent",  # Name of your agent
+    system_prompt="You are a helpful assistant",  # Agent's system prompt
+    mcp_servers=[mcp_params],  # List of MCP server configurations
+    max_loops=5,  # Maximum number of loops for task execution
+    verbose=True  # Enable verbose output
+)
+
+# Run the agent
+result = agent.run("Your task here")
+print(result)
+```
+
+## Required Parameters
+
+1. **MCP Server Parameters**:
+   - `url`: The SSE endpoint of your MCP server
+   - `headers`: Must include `Accept: text/event-stream`
+   - `timeout`: Connection timeout in seconds
+
+2. **Agent Parameters**:
+   - `agent_name`: Name of your agent
+   - `system_prompt`: Agent's system prompt
+   - `mcp_servers`: List of MCP server configurations
+   - `max_loops`: Maximum number of loops for task execution
+   - `verbose`: Enable verbose output for debugging
+
+## Example Usage
+
+```python
+# Create agent
+agent = Agent(
+    agent_name="math_agent",
+    system_prompt="You are a math assistant",
+    mcp_servers=[mcp_params],
+    max_loops=5,
+    verbose=True
+)
+
+# Run a math task
+result = agent.run("Add 5 and 3")
+print(result)  # Should return 8
+``` 
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