Documentation Index
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Servers can send log messages to clients during tool execution. This provides visibility into server operations and helps with debugging.
Handler
from dedalus_mcp.client import ClientCapabilitiesConfig, open_connection
from dedalus_mcp.types import LoggingMessageNotificationParams
def logging_handler(params: LoggingMessageNotificationParams) -> None:
"""Handle log messages from the server."""
level = params.level.upper()
data = params.data
print(f"[{level}] {data}")
Usage
capabilities = ClientCapabilitiesConfig(logging=logging_handler)
async with open_connection(
url="http://127.0.0.1:8000/mcp",
transport="streamable-http",
capabilities=capabilities,
) as client:
# Server logs will be routed to your handler
result = await client.call_tool("process", {"file": "data.csv"})
Log Levels
Servers can send logs at different levels:
| Level | Description |
|---|
debug | Detailed debugging information |
info | General operational messages |
warning | Warning conditions |
error | Error conditions |
Structured Logging
Route to your logging framework:
import logging
logger = logging.getLogger("mcp.server")
def logging_handler(params: LoggingMessageNotificationParams) -> None:
level = getattr(logging, params.level.upper(), logging.INFO)
logger.log(level, params.data)
Full Example
import asyncio
from dedalus_mcp.client import ClientCapabilitiesConfig, open_connection
from dedalus_mcp.types import LoggingMessageNotificationParams
def logging_handler(params: LoggingMessageNotificationParams) -> None:
level = params.level.upper()
print(f"[SERVER {level}] {params.data}")
async def main():
capabilities = ClientCapabilitiesConfig(logging=logging_handler)
async with open_connection(
url="http://127.0.0.1:8000/mcp",
transport="streamable-http",
capabilities=capabilities,
) as client:
print(f"Connected: {client.initialize_result.serverInfo.name}")
tools = await client.list_tools()
print(f"Available tools: {[t.name for t in tools.tools]}")
# Call a tool - logs will appear via handler
result = await client.call_tool("analyze", {"input": "test"})
print(f"Result: {result.content}")
asyncio.run(main())
