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import os
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import json
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from swarms import Agent
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import io
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import sys
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from contextlib import redirect_stdout
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print("\n=== Testing Multiple MCP Tool Execution ===\n")
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# Configure multiple MCP URLs
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os.environ["MCP_URLS"] = "http://localhost:8000/sse,http://localhost:9001/sse"
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def capture_output(func):
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"""Capture printed output from a function"""
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f = io.StringIO()
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with redirect_stdout(f):
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func()
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return f.getvalue()
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def test_direct_tool_execution():
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"""Test directly executing tools on different MCP servers"""
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print("Testing direct tool execution...\n")
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agent = Agent(
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agent_name="Multi-MCP-Agent",
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model_name="gpt-4o-mini",
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max_loops=1
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)
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# Create JSON payloads for multiple tools
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payloads = [
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{
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"function_name": "get_weather",
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"server_url": "http://localhost:8000/sse",
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"payload": {"city": "Paris"}
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},
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{
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"function_name": "get_news",
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"server_url": "http://localhost:9001/sse",
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"payload": {"topic": "science"}
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}
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]
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# Execute the tools and capture output
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print("Executing tools on multiple MCP servers...")
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output = capture_output(
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lambda: agent.handle_multiple_mcp_tools(agent.mcp_urls, json.dumps(payloads))
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)
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# Extract and display results
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print("\nResults from MCP tools:")
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print(output)
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print("\nTest complete - Multiple MCP execution successful!")
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def test_agent_configuration():
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"""Test different ways to configure agents with multiple MCP URLs"""
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print("\n=== Testing Agent MCP Configuration Methods ===\n")
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# Method 1: Configure via environment variables (already set above)
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agent1 = Agent(agent_name="Env-Config-Agent")
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print(f"Agent1 MCP URLs (from env): {agent1.mcp_urls}")
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# Method 2: Configure via direct parameter
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agent2 = Agent(
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agent_name="Direct-Config-Agent",
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mcp_urls=["http://localhost:8000/sse", "http://localhost:9001/sse"]
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)
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print(f"Agent2 MCP URLs (from param): {agent2.mcp_urls}")
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if __name__ == "__main__":
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test_agent_configuration()
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test_direct_tool_execution()
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