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Tools are server-side functions that a client can execute with arguments. With MCPClient, the basic flow is:

​
List tools

Discover available tools on the server: 
from dedalus_mcp.client import open_connection

async with open_connection("http://127.0.0.1:8000/mcp") as client:
    tools = await client.list_tools()

    for tool in tools.tools:
        print(f"{tool.name}: {tool.description}")

​
Tool schema

Each tool includes:
FieldTypeDescription
namestrTool identifier
descriptionstrWhat the tool does
inputSchemadictJSON Schema for arguments
for tool in tools.tools:
    print(f"Name: {tool.name}")
    print(f"Description: {tool.description}")
    print(f"Parameters schema: {tool.inputSchema}")

​
Call tools

Execute a tool with arguments: 
result = await client.call_tool("add", {"a": 5, "b": 3})

# Tool results are content blocks; most tools return TextContent.
print(result.content[0].text)

​
Error handling

If the server returns a JSON-RPC error (common when a tool raises), call_tool(...) raises McpError: 
from mcp.shared.exceptions import McpError

try:
    result = await client.call_tool("divide", {"a": 10, "b": 0})
    print(result.content[0].text)
except McpError as e:
    print(f"Tool call failed: {e}")

​
Example: Calculator

import asyncio
from dedalus_mcp.client import MCPClient
from mcp.shared.exceptions import McpError

async def main():
    client = await MCPClient.connect("http://127.0.0.1:8000/mcp")
    try:
        tools = await client.list_tools()
        print("Available tools:")
        for tool in tools.tools:
            print(f"  - {tool.name}")

        add_result = await client.call_tool("add", {"a": 5, "b": 3})
        print(f"5 + 3 = {add_result.content[0].text}")

        mul_result = await client.call_tool("multiply", {"a": 4, "b": 7})
        print(f"4 * 7 = {mul_result.content[0].text}")

    except McpError as e:
        print(f"Tool call failed: {e}")
    finally:
        await client.close()

asyncio.run(main())

​
Context manager

open_connection(...) is an async context manager. It means you don’t have to remember to call await client.close(). When the async with block exits, it automatically closes the underlying connection for you. 
from dedalus_mcp.client import open_connection

async with open_connection("http://127.0.0.1:8000/mcp") as client:
    tools = await client.list_tools()
    result = await client.call_tool("greet", {"name": "World"})
    print(result.content[0].text)
Last modified on January 27, 2026