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client.py
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124 lines (91 loc) · 4.06 KB
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import sys
import asyncio
from typing import Optional
from contextlib import AsyncExitStack
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
from langchain_mcp_adapters.tools import load_mcp_tools
from langgraph.prebuilt import create_react_agent
from langchain.schema import HumanMessage, SystemMessage, AIMessage
from dotenv import load_dotenv
load_dotenv() # load environment variables from .env
class MCPClient:
def __init__(self):
# Initialize session and client objects
self.session: Optional[ClientSession] = None
self.exit_stack = AsyncExitStack()
async def connect_to_server(self, server_script_path: str):
"""Connect to an MCP server
Args:
server_script_path: Path to the server script (.py or .js)
"""
is_python = server_script_path.endswith('.py')
is_js = server_script_path.endswith('.js')
if not (is_python or is_js):
raise ValueError("Server script must be a .py or .js file")
command = "python" if is_python else "node"
server_params = StdioServerParameters(
command=command,
args=[server_script_path],
env=None
)
stdio_transport = await self.exit_stack.enter_async_context(stdio_client(server_params))
self.stdio, self.write = stdio_transport
self.session = await self.exit_stack.enter_async_context(ClientSession(self.stdio, self.write))
await self.session.initialize()
# List available tools
response = await self.session.list_tools()
tools = response.tools
print("\nConnected to server with tools:", [tool.name for tool in tools])
async def process_query(self, query: str) -> str:
"""Process a query using Claude and available tools"""
chat_history = [HumanMessage(content=query)]
tools = await load_mcp_tools(self.session)
# Create and run the agent
agent = create_react_agent("google_genai:gemini-2.0-flash", tools)
# Process response and handle tool calls
final_text = []
# initial call to the agent with first query
agent_response = await agent.ainvoke({"messages": chat_history})
for content in agent_response['messages']:
if content.type == 'ai':
final_text.append(content.content)
chat_history.append(AIMessage(content=content.content))
dict_func = content.additional_kwargs
if dict_func:
final_text.append(f"[Function call: {dict_func['function_call']['name']} with args {dict_func['function_call']['arguments']}]")
elif content.type == 'tool':
final_text.append(content.content)
chat_history.append(HumanMessage(content=content.content))
agent_response = await agent.ainvoke({'messages':chat_history})
final_text.append(agent_response['messages'].content)
return "\n".join(final_text)
async def chat_loop(self):
"""Run an interactive chat loop"""
print("\nMCP Client Started!")
print("Type your queries or 'quit' to exit.")
while True:
try:
query = input("\nQuery: ").strip()
if query.lower() == 'quit':
break
response = await self.process_query(query)
print(response)
except Exception as e:
print(f"\nError: {str(e)}")
async def cleanup(self):
"""Clean up resources"""
await self.exit_stack.aclose()
async def main():
if len(sys.argv) < 2:
print("Usage: python client.py <path_to_server_script>")
sys.exit(1)
client = MCPClient()
try:
await client.connect_to_server(sys.argv[1])
await client.chat_loop()
finally:
await client.cleanup()
if __name__ == "__main__":
import sys
asyncio.run(main())