import asyncio
from agents import Agent, Runner, set_default_openai_client
from agents.mcp import MCPServerStreamableHttp
from openai import AsyncOpenAI
from openai.types.responses import ResponseTextDeltaEvent
import os
from dotenv import load_dotenv
load_dotenv()
async def main():
# Set up OpenAI client
client = AsyncOpenAI(api_key=os.getenv('OPENAI_API_KEY'))
set_default_openai_client(client)
# Instantiate the MCP server connection to Observee
# Replace {your_client_id} with your actual client ID from the Observee dashboard
mcp_server = MCPServerStreamableHttp(
name='Observee',
params={
'url': 'https://mcp.observee.ai/mcp?client_id={your_client_id}',
'headers': {
'Authorization': 'Bearer {observee_api_key}' # Replace with your API key
}
}
)
# Create the Agent and register the MCP server
agent = Agent(
name='Observee Agent',
instructions='Use all available tools and knowledge to help users with their requests.',
mcp_servers=[mcp_server]
)
try:
# Use MCP server as async context manager
async with mcp_server:
# Example query with streaming - the Agent will use appropriate Observee tools
result = Runner.run_streamed(
agent,
'check my latest emails'
)
# Stream the response as it comes
async for event in result.stream_events():
if event.type == "raw_response_event" and isinstance(event.data, ResponseTextDeltaEvent):
print(event.data.delta, end="", flush=True)
print() # Final newline
except Exception as error:
print(f'Connection failed: {error}')
# Check your client ID, API key, and network connection
if __name__ == "__main__":
asyncio.run(main())
