import asyncio
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
from langchain_mcp_adapters.client import MultiServerMCPClient
from dotenv import load_dotenv
import os
load_dotenv()
async def main():
# Configure MCP client
client = MultiServerMCPClient({
"bright_data": {
"url": "https://mcp.brightdata.com/sse?token=<API_TOKEN>",
"transport": "sse",
}
})
# Get available tools
tools = await client.get_tools()
print("Available tools:", [tool.name for tool in tools])
# Configure LLM
llm = ChatOpenAI(
openai_api_key=os.getenv("OPENROUTER_API_KEY"),
openai_api_base="https://openrouter.ai/api/v1",
model_name="moonshotai/kimi-k2"
)
# System prompt for web search agent
system_prompt = """
You are a web search agent with comprehensive scraping capabilities. Your tools include:
- **search_engine**: Get search results from Google/Bing/Yandex
- **scrape_as_markdown**: Extract content from any webpage with bot detection bypass
- **Structured extractors**: Fast, reliable data from major platforms (Amazon, LinkedIn, Instagram, Facebook, X, TikTok, YouTube, Reddit, Zillow, etc.)
- **Browser automation**: Navigate, click, type, screenshot for complex interactions
Guidelines:
- Use structured web_data_* tools for supported platforms when possible (faster/more reliable)
- Use general scraping for other sites
- Handle errors gracefully and respect rate limits
- Think step by step about what information you need and which tools to use
- Be thorough in your research and provide comprehensive answers
When responding, follow this pattern:
1. Think about what information is needed
2. Choose the appropriate tool(s)
3. Execute the tool(s)
4. Analyze the results
5. Provide a clear, comprehensive answer
"""
# Create ReAct agent
agent = create_react_agent(
model=llm,
tools=tools,
prompt=system_prompt
)
# Test the agent
print("Testing ReAct Agent with available tools...")
print("=" * 50)
result = await agent.ainvoke({
"messages": [("human", "Search for the latest news about AI developments")]
})
print("\nAgent Response:")
print(result["messages"][-1].content)
if __name__ == "__main__":
asyncio.run(main())
