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import asyncio
import os
import json
from typing import List, Dict, Any, Union
from contextlib import AsyncExitStack
import gradio as gr
from gradio.components.chatbot import ChatMessage
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
from anthropic import Anthropic
from dotenv import load_dotenv
load_dotenv()
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
class MCPClientWrapper:
def __init__(self):
self.session = None
self.exit_stack = None
self.anthropic = Anthropic()
self.tools = []
def connect(self, server_path: str) -> str:
return loop.run_until_complete(self._connect(server_path))
async def _connect(self, server_path: str) -> str:
if self.exit_stack:
await self.exit_stack.aclose()
self.exit_stack = AsyncExitStack()
is_python = server_path.endswith('.py')
command = "python" if is_python else "node"
nasa_api_key = os.getenv("NASA_API_KEY")
server_params = StdioServerParameters(
command=command,
args=[server_path],
env={"PYTHONIOENCODING": "utf-8", "PYTHONUNBUFFERED": "1", "NASA_API_KEY": nasa_api_key}
)
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()
response = await self.session.list_tools()
self.tools = [{
"name": tool.name,
"description": tool.description,
"input_schema": tool.inputSchema
} for tool in response.tools]
tool_names = [tool["name"] for tool in self.tools]
return f"Connected to DOOMSWEEK MCP server. Available tools: {', '.join(tool_names)}"
def process_message(self, message: str, history: List[Union[Dict[str, Any], ChatMessage]]) -> tuple:
if not self.session:
return history + [
{"role": "user", "content": message},
{"role": "assistant", "content": "Please connect to an MCP server first."}
], gr.Textbox(value="")
new_messages = loop.run_until_complete(self._process_query(message, history))
return history + [{"role": "user", "content": message}] + new_messages, gr.Textbox(value="")
async def _process_query(self, message: str, history: List[Union[Dict[str, Any], ChatMessage]]):
claude_messages = []
for msg in history:
if isinstance(msg, ChatMessage):
role, content = msg.role, msg.content
else:
role, content = msg.get("role"), msg.get("content")
if role in ["user", "assistant", "system"]:
claude_messages.append({"role": role, "content": content})
claude_messages.append({"role": "user", "content": message})
response = self.anthropic.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=1000,
messages=claude_messages,
tools=self.tools
)
result_messages = []
for content in response.content:
if content.type == 'text':
result_messages.append({
"role": "assistant",
"content": content.text
})
elif content.type == 'tool_use':
tool_name = content.name
tool_args = content.input
result_messages.append({
"role": "assistant",
"content": f"I'll use the {tool_name} tool to help answer your question.",
"metadata": {
"title": f"Using tool: {tool_name}",
"log": f"Parameters: {json.dumps(tool_args, ensure_ascii=True)}",
"status": "pending",
"id": f"tool_call_{tool_name}"
}
})
result_messages.append({
"role": "assistant",
"content": "```json\n" + json.dumps(tool_args, indent=2, ensure_ascii=True) + "\n```",
"metadata": {
"parent_id": f"tool_call_{tool_name}",
"id": f"params_{tool_name}",
"title": "Tool Parameters"
}
})
result = await self.session.call_tool(tool_name, tool_args)
if result_messages and "metadata" in result_messages[-2]:
result_messages[-2]["metadata"]["status"] = "done"
result_messages.append({
"role": "assistant",
"content": "Here are the results from the tool:",
"metadata": {
"title": f"Tool Result for {tool_name}",
"status": "done",
"id": f"result_{tool_name}"
}
})
result_content = result.content
if isinstance(result_content, list):
result_content = "\n".join(str(item) for item in result_content)
try:
result_json = json.loads(result_content)
if isinstance(result_json, dict) and "type" in result_json:
if result_json["type"] == "image" and "url" in result_json:
result_messages.append({
"role": "assistant",
"content": {"path": result_json["url"], "alt_text": result_json.get("message", "Generated image")},
"metadata": {
"parent_id": f"result_{tool_name}",
"id": f"image_{tool_name}",
"title": "Generated Image"
}
})
else:
result_messages.append({
"role": "assistant",
"content": "```\n" + result_content + "\n```",
"metadata": {
"parent_id": f"result_{tool_name}",
"id": f"raw_result_{tool_name}",
"title": "Raw Output"
}
})
except:
result_messages.append({
"role": "assistant",
"content": "```\n" + result_content + "\n```",
"metadata": {
"parent_id": f"result_{tool_name}",
"id": f"raw_result_{tool_name}",
"title": "Raw Output"
}
})
claude_messages.append({"role": "user", "content": f"Tool result for {tool_name}: {result_content}"})
next_response = self.anthropic.messages.create(
model="claude-3-5-sonnet-20241022",
max_tokens=1000,
messages=claude_messages,
)
if next_response.content and next_response.content[0].type == 'text':
result_messages.append({
"role": "assistant",
"content": next_response.content[0].text
})
return result_messages
client = MCPClientWrapper()
def gradio_interface():
with gr.Blocks(title="MCP Doomsweek Assistant", css_paths=["styles.css"],) as demo:
title_html = """
<style>
@font-face {
font-family: Monitorica;
src: url("/gradio_api/file=monitorica.bold.otf") format("opentype");
font-weight: Regular;
font-style: normal;
}
</style>
<center>
<div><h1 style='font-family: Monitorica; font-size: 42px;'> Your <span class='skew-shake-x'>Doomsweek</span> MCP Assistant </h1>
</center></div>
"""
with gr.Row():
title = gr.HTML(title_html)
gr.Markdown("**Note: this space was made for the MCP Hackathon in June 2025 and will stop working when the connected credits run out. Further development of this agent will take place on my [Huggingface Profile](https://huggingface.co/crcdng). Thanks for trying ot Doomsweek Assistant.**")
with gr.Row():
title = gr.Image("space_svgrepo_com_small.jpg")
gr.Markdown("What is more important than to know one's own end? This space will answer ultimate questions. In particular will you know if humanity will survive the next 7 days. To do that, **first connect via MCP to the DOOMSWEEK MCP Server**. The server fetches data from the NASA Near Earth Object Web Service and checks if ... we are doomed. Anthropic's Claude will give you the result in nice words, hopefully. In other words, before an Asteroid will smash this planet you will learn it here first. Nice, isn't it? You will have enough time to enjoy a scoop of your favourate ice cream, walk the dog a last time and sell all tech stocks. You won't need them, promised. Try it out and **chat with the assistant (examples below)**.")
with gr.Row(equal_height=True):
with gr.Column(scale=4):
server_path = gr.Textbox(
label="Server Script Path",
placeholder="Enter path to server script (e.g., doomsweek_mcp_server.py)",
value="doomsweek_mcp_server.py"
)
with gr.Column(scale=1):
connect_btn = gr.Button("Connect", variant='secondary')
status = gr.Textbox(label="Connection Status", interactive=False)
chatbot = gr.Chatbot(
value=[],
height=500,
type="messages",
show_copy_button=True,
avatar_images=("agent_a.jpg", "agent_b.jpg")
)
with gr.Row(equal_height=True):
msg = gr.Textbox(
label="Your Question about Humanity's Fate",
placeholder="Ask (e.g., 'How likely is it that humanity will survive the next week?')",
scale=4
)
clear_btn = gr.Button("Clear Chat", scale=1)
connect_btn.click(client.connect, inputs=server_path, outputs=status)
msg.submit(client.process_message, [msg, chatbot], [chatbot, msg])
clear_btn.click(lambda: [], None, chatbot)
examples = gr.Examples(
examples=[
["Tell me about the probability of doom in the next week."],
["How likely is it that humanity will survive the next week?"],
["Will asteroids destroy the earth next week?"],
],
inputs=[msg],
)
return demo
if __name__ == "__main__":
if not os.getenv("ANTHROPIC_API_KEY"):
print("Warning: ANTHROPIC_API_KEY not found in environment. Please set it in your .env file.")
interface = gradio_interface()
interface.launch(debug=True, allowed_paths=["monitorica.bold.otf", "agent_a.jpg", "agent_b.jpg", "space_svgrepo_com_small.jpg", "styles.css"],) |