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"""
ClimateQA MCP Client - Test and interact with the ClimateQA MCP server.
This script demonstrates how to connect to the ClimateQA MCP server using
the OpenAI Agents SDK and query climate-related documents and graphs.
Usage:
# List available MCP tools
python scripts/mcp_client.py list-tools
# Run a single query
python scripts/mcp_client.py query "What causes climate change?"
# Interactive chat mode
python scripts/mcp_client.py interactive
# Custom MCP server URL
python scripts/mcp_client.py --url http://localhost:7960/gradio_api/mcp/sse query "..."
Requirements:
pip install openai-agents
Environment:
OPENAI_API_KEY: Required for the agent
MCP_SERVER_URL: Optional, defaults to http://localhost:7960/gradio_api/mcp/sse
"""
from __future__ import annotations
import argparse
import asyncio
import json
import os
import sys
from typing import TYPE_CHECKING
# Load environment variables
try:
from dotenv import load_dotenv
load_dotenv()
except ImportError:
pass
if TYPE_CHECKING:
from agents import Agent
from agents.mcp import MCPServerSse
# Configuration
DEFAULT_MCP_URL = "http://localhost:7960/gradio_api/mcp/sse"
DEFAULT_MODEL = "gpt-4o-mini"
TOOL_RESULT_PREVIEW_LENGTH = 500
def get_mcp_url() -> str:
"""Get the MCP server URL from environment or default."""
return os.getenv("MCP_SERVER_URL", DEFAULT_MCP_URL)
def check_api_key() -> None:
"""Verify OpenAI API key is set."""
if not os.getenv("OPENAI_API_KEY"):
print("β Error: OPENAI_API_KEY environment variable is required")
print(" Set it with: export OPENAI_API_KEY='your-key'")
sys.exit(1)
def create_mcp_server(url: str) -> "MCPServerSse":
"""Create an MCP server connection."""
from agents.mcp import MCPServerSse
return MCPServerSse(
params={"url": url},
name="climateqa",
cache_tools_list=True,
)
def create_agent(mcp_server: "MCPServerSse") -> "Agent":
"""Create the ClimateQA agent with MCP tools."""
from agents import Agent
return Agent(
name="ClimateQA Agent",
instructions="""You are a climate research assistant with access to scientific
documents from IPCC, IPBES, IPOS reports and graphs from IEA and OWID.
When answering climate-related questions:
1. Use retrieve_data_mcp to get relevant documents and figures from climate reports
2. Use retrieve_graphs_mcp to get relevant data visualizations
3. Synthesize the information into a clear, well-sourced answer
Always cite your sources and mention which reports the information comes from.""",
mcp_servers=[mcp_server],
model=DEFAULT_MODEL,
)
async def list_tools(url: str) -> None:
"""List all available MCP tools from the server."""
print(f"\nπ‘ Connecting to: {url}")
print("=" * 60)
mcp_server = create_mcp_server(url)
async with mcp_server:
tools = await mcp_server.list_tools()
if not tools:
print("β οΈ No tools found on this MCP server")
return
print(f"Found {len(tools)} tool(s):\n")
for tool in tools:
print(f"π {tool.name}")
if tool.description:
print(f" {tool.description}")
if tool.inputSchema:
schema = json.dumps(tool.inputSchema, indent=2)
print(f" Schema: {schema}")
print()
async def run_query(url: str, query: str) -> None:
"""Run a single query through the agent."""
from agents import Runner
check_api_key()
print(f"\nπ‘ MCP Server: {url}")
print(f"β Query: {query}")
print("=" * 60)
mcp_server = create_mcp_server(url)
agent = create_agent(mcp_server)
async with mcp_server:
result = Runner.run_streamed(agent, query)
async for event in result.stream_events():
if event.type == "run_item_stream_event":
item = event.item
item_type = getattr(item, "type", None)
if item_type == "tool_call_item":
name = getattr(item, "name", "unknown")
args = getattr(item, "arguments", "{}")
print(f"\nπ§ Calling: {name}")
print(f" Args: {_truncate(str(args), 200)}")
elif item_type == "tool_call_output_item":
output = getattr(item, "output", "")
print(f"\nπ₯ Result preview:")
print(f" {_truncate(str(output), TOOL_RESULT_PREVIEW_LENGTH)}")
print("\n" + "=" * 60)
print("π€ Agent Response:")
print("=" * 60)
print(result.final_output)
async def interactive_mode(url: str) -> None:
"""Run the agent in interactive chat mode."""
from agents import Runner
check_api_key()
print("\n" + "=" * 60)
print("π ClimateQA MCP Agent - Interactive Mode")
print("=" * 60)
print(f"π‘ Server: {url}")
print("π‘ Type your questions (or 'quit' to exit)")
print("=" * 60)
mcp_server = create_mcp_server(url)
agent = create_agent(mcp_server)
async with mcp_server:
while True:
try:
query = input("\nβ You: ").strip()
if query.lower() in ("quit", "exit", "q"):
print("π Goodbye!")
break
if not query:
continue
print("\nβ³ Thinking...")
result = Runner.run_streamed(agent, query)
async for event in result.stream_events():
if event.type == "run_item_stream_event":
item = event.item
item_type = getattr(item, "type", None)
if item_type == "tool_call_item":
name = getattr(item, "name", "unknown")
print(f" π§ Using: {name}")
elif item_type == "tool_call_output_item":
output = getattr(item, "output", "")
print(f" π₯ Got {len(str(output))} chars")
print(f"\nπ€ Agent: {result.final_output}")
except KeyboardInterrupt:
print("\n\nπ Interrupted. Goodbye!")
break
except Exception as e:
print(f"\nβ Error: {e}")
def _truncate(text: str, length: int) -> str:
"""Truncate text with ellipsis if too long."""
if len(text) <= length:
return text
return text[:length] + "..."
def main() -> None:
"""Main entry point."""
parser = argparse.ArgumentParser(
description="ClimateQA MCP Client - Query climate documents via MCP",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
Examples:
%(prog)s list-tools # List available MCP tools
%(prog)s query "What causes global warming?" # Run a single query
%(prog)s interactive # Interactive chat mode
%(prog)s --url http://host:7960/... query .. # Use custom server URL
""",
)
parser.add_argument(
"--url",
type=str,
default=None,
help=f"MCP server URL (default: {DEFAULT_MCP_URL})",
)
subparsers = parser.add_subparsers(dest="command", help="Command to run")
# list-tools command
subparsers.add_parser("list-tools", help="List available MCP tools")
# query command
query_parser = subparsers.add_parser("query", help="Run a single query")
query_parser.add_argument("text", type=str, help="The question to ask")
# interactive command
subparsers.add_parser("interactive", help="Interactive chat mode")
args = parser.parse_args()
# Determine URL
url = args.url or get_mcp_url()
if args.command == "list-tools":
asyncio.run(list_tools(url))
elif args.command == "query":
asyncio.run(run_query(url, args.text))
elif args.command == "interactive":
asyncio.run(interactive_mode(url))
else:
parser.print_help()
if __name__ == "__main__":
main() |