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Version: 0.0.2

Logging System

This guide covers the centralized logging system architecture, programmatic usage, and best practices for developers contributing to the Slack MCP Server project.

Architecture Overview​

The logging system is split into two separate configurations:

Source Code Logging (slack_mcp/logging/)​

For production application logging with features like:

  • Console and file logging
  • Automatic log rotation
  • Hierarchical configuration
  • Environment variable support
  • Case-insensitive log levels

Test Logging (test/logging/)​

For test execution logging with:

  • Clean output (WARNING level by default)
  • Verbose mode for debugging
  • Simple format for test readability
  • External library silencing

Programmatic Usage​

Basic Setup​

from slack_mcp.logging import setup_logging
import logging

# Basic setup (console only)
setup_logging(level="INFO")

# Get logger for your module
logger = logging.getLogger(__name__)

# Use logger
logger.info("Application started")
logger.debug("Debug information")
logger.error("Error occurred")

With File Logging​

from slack_mcp.logging import setup_logging

# Setup with file logging
setup_logging(
    level="DEBUG",
    log_file="/path/to/app.log"
)

Full Custom Configuration​

from slack_mcp.logging import setup_logging

setup_logging(
    level="INFO",
    log_file="/var/log/slack-mcp.log",
    log_format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
    date_format="%Y-%m-%d %H:%M:%S"
)

CLI Integration​

The logging system provides helper functions for argparse integration:

import argparse
from slack_mcp.logging import add_logging_arguments, setup_logging_from_args

# Create parser
parser = argparse.ArgumentParser()

# Add your arguments
parser.add_argument("--port", type=int, default=8000)

# Add logging arguments (--log-level, --log-file, --log-dir, --log-format)
parser = add_logging_arguments(parser)

# Parse arguments
args = parser.parse_args()

# Setup logging from arguments
setup_logging_from_args(args)

Module-Level Logging​

Best Practice​

Always use __name__ for module-level loggers:

import logging

# At module level
logger = logging.getLogger(__name__)

def my_function():
    logger.info("Function called")
    logger.debug("Processing data...")

This creates a hierarchical logger structure:

  • slack_mcp.mcp.server → Logs from MCP server
  • slack_mcp.webhook.server → Logs from webhook server
  • slack_mcp.client.manager → Logs from client manager

Logger Hierarchy​

The logging configuration automatically manages logger hierarchy:

# Root logger
logging.getLogger()  # Catches everything

# Package logger
logging.getLogger("slack_mcp")  # All slack_mcp logs

# Module logger
logging.getLogger("slack_mcp.mcp.server")  # Specific module logs

Available Functions and Constants​

Functions​

setup_logging(level, log_file, log_format, date_format)​

Configure application logging.

Parameters:

  • level (str): Log level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
  • log_file (str, optional): Path to log file
  • log_format (str, optional): Custom log format
  • date_format (str, optional): Custom date format
setup_logging(
    level="INFO",
    log_file="app.log",
    log_format="%(asctime)s %(message)s"
)

setup_logging_from_args(args)​

Setup logging from parsed command-line arguments.

Parameters:

  • args: Namespace from argparse with logging attributes
args = parser.parse_args()
setup_logging_from_args(args)

add_logging_arguments(parser)​

Add logging arguments to argparse parser.

Parameters:

  • parser: ArgumentParser instance

Returns: Modified parser with logging arguments

Added Arguments:

  • --log-level: Case-insensitive log level
  • --log-file: Log file path
  • --log-dir: Log directory
  • --log-format: Custom log format
parser = add_logging_arguments(parser)

get_logging_config(level, log_file, log_format, date_format)​

Get logging configuration dictionary for logging.config.dictConfig().

from slack_mcp.logging import get_logging_config
import logging.config

config = get_logging_config(level="DEBUG", log_file="app.log")
logging.config.dictConfig(config)

get_log_file_path(log_dir, log_file)​

Get absolute log file path from directory and filename.

from slack_mcp.logging import get_log_file_path

path = get_log_file_path(
    log_dir="/var/log/slack-mcp",
    log_file="server.log"
)
# Returns: /var/log/slack-mcp/server.log

Constants​

from slack_mcp.logging import (
    DEFAULT_LOG_FORMAT,
    DEFAULT_DATE_FORMAT,
    DEFAULT_LEVEL,
    LOG_LEVELS,
    DEFAULT_LOG_DIR,
    DEFAULT_LOG_FILE,
)

# Default values
DEFAULT_LOG_FORMAT = "%(asctime)s [%(levelname)8s] %(name)s: %(message)s"
DEFAULT_DATE_FORMAT = "%Y-%m-%d %H:%M:%S"
DEFAULT_LEVEL = "INFO"
DEFAULT_LOG_DIR = "logs"
DEFAULT_LOG_FILE = "slack_mcp.log"
LOG_LEVELS = ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]

Test Logging​

Setup Test Logging​

from test.logging import setup_test_logging

# Basic test logging (WARNING level to reduce noise)
setup_test_logging()

# Verbose test logging (INFO level for debugging)
setup_test_logging(verbose=True)

# Custom log level
setup_test_logging(level="DEBUG")

Get Test Logger​

from test.logging import get_test_logger

logger = get_test_logger(__name__)
logger.info("Test started")

Pytest Configuration​

Control test logging with pytest flags:

# Verbose test output
pytest -v --log-cli-level=DEBUG

# With environment variable
TEST_LOG_LEVEL=DEBUG pytest -v

Log File Configuration​

Rotation Settings​

Automatic rotation is configured with:

{
    "class": "logging.handlers.RotatingFileHandler",
    "filename": log_file_path,
    "maxBytes": 10 * 1024 * 1024,  # 10MB
    "backupCount": 5,
    "formatter": "default",
}

Behavior:

  • Rotates at 10MB
  • Keeps 5 backup files
  • Oldest file deleted on rotation

Custom Handlers​

Add custom handlers to the logging configuration:

import logging
from slack_mcp.logging import get_logging_config

# Get base config
config = get_logging_config(level="INFO")

# Add custom handler
config["handlers"]["custom"] = {
    "class": "logging.StreamHandler",
    "formatter": "default",
    "stream": "ext://sys.stderr",
}

# Apply configuration
logging.config.dictConfig(config)

Case-Insensitive Log Levels​

The logging system uses type=str.upper in argparse to automatically convert log level input:

log_group.add_argument(
    "--log-level",
    dest="log_level",
    type=str.upper,  # Converts to uppercase automatically
    default=os.getenv("LOG_LEVEL", DEFAULT_LEVEL),
    choices=LOG_LEVELS,
    help=f"Set the logging level (default: {DEFAULT_LEVEL})",
)

This allows users to type:

  • --log-level debug → Converted to DEBUG
  • --log-level INFO → Stays INFO
  • --log-level Warning → Converted to WARNING

Migration Guide​

From Old logging.basicConfig()​

Old Code:

import logging
logging.basicConfig(level=logging.INFO)

New Code:

from slack_mcp.logging import setup_logging
setup_logging(level="INFO")

From Manual CLI Parsing​

Old Code:

args = parse_args()
logging.basicConfig(level=args.log_level.upper())

New Code:

from slack_mcp.logging import setup_logging_from_args
args = parse_args()
setup_logging_from_args(args)

External Library Management​

The logging system automatically reduces noise from external libraries:

"loggers": {
    "uvicorn": {
        "handlers": ["console"],
        "level": "ERROR",
        "propagate": False,
    },
    "httpx": {
        "handlers": ["console"],
        "level": "ERROR",
        "propagate": False,
    },
    "asyncio": {
        "handlers": ["console"],
        "level": "WARNING",
        "propagate": False,
    },
}

This keeps logs clean while still capturing critical errors.

Best Practices​

1. Always Use __name__​

# Good
logger = logging.getLogger(__name__)

# Bad - hardcoded name
logger = logging.getLogger("my_module")

2. Log at Appropriate Levels​

# DEBUG - Detailed diagnostic info
logger.debug(f"Processing request with params: {params}")

# INFO - General information
logger.info("Server started successfully")

# WARNING - Potentially problematic
logger.warning("Rate limit approaching threshold")

# ERROR - Serious problems
logger.error(f"Failed to connect: {error}")

# CRITICAL - Fatal problems
logger.critical("Database connection lost, shutting down")

3. Use Lazy Formatting​

# Good - only formats if logged
logger.debug("Processing %s items", len(items))

# Bad - always formats
logger.debug(f"Processing {len(items)} items")

4. Include Context​

# Good - includes context
logger.error(f"Failed to process message {message_id}: {error}")

# Bad - missing context
logger.error("Processing failed")

5. Don't Log Sensitive Data​

# Bad - logs sensitive token
logger.info(f"Using token: {slack_token}")

# Good - masks sensitive data
logger.info(f"Using token: {slack_token[-4:]}")

6. Test Logging Configuration​

Write tests for logging behavior:

def test_logging_setup(caplog):
    """Test that logging is configured correctly."""
    from slack_mcp.logging import setup_logging
    
    setup_logging(level="DEBUG")
    
    logger = logging.getLogger("test_module")
    logger.debug("Test message")
    
    assert "Test message" in caplog.text

Environment-Specific Configuration​

Development​

from slack_mcp.logging import setup_logging

if os.getenv("ENV") == "development":
    setup_logging(level="DEBUG")
else:
    setup_logging(
        level="INFO",
        log_file="/var/log/slack-mcp/production.log"
    )

Testing​

# In test fixtures
@pytest.fixture(autouse=True)
def setup_test_logs():
    """Setup logging for tests."""
    from test.logging import setup_test_logging
    setup_test_logging(verbose=False)

Production​

from slack_mcp.logging import setup_logging

setup_logging(
    level=os.getenv("LOG_LEVEL", "INFO"),
    log_file=os.getenv("LOG_FILE", "/var/log/slack-mcp/server.log"),
)

Troubleshooting​

Logs Not Appearing​

  1. Check logger name: Ensure using __name__
  2. Verify log level: Message level must be >= configured level
  3. Check configuration: Ensure setup_logging() was called

Duplicate Logs​

If seeing duplicate log messages:

# Ensure propagate=False in logger config
"loggers": {
    "slack_mcp": {
        "handlers": ["console"],
        "level": level,
        "propagate": False,  # Prevents duplicate logs
    }
}

Performance Issues​

High log volume impacting performance:

  1. Increase log level (INFO → WARNING)
  2. Disable DEBUG logging in hot code paths
  3. Use lazy formatting
  4. Consider async logging for high-throughput

Advanced Usage​

Custom Formatter​

import logging
from slack_mcp.logging import setup_logging

# Custom formatter class
class CustomFormatter(logging.Formatter):
    def format(self, record):
        # Add custom logic
        return super().format(record)

# Apply after setup
setup_logging(level="INFO")
handler = logging.getLogger().handlers[0]
handler.setFormatter(CustomFormatter("%(message)s"))

Structured Logging​

For JSON logging:

import json
import logging

class JSONFormatter(logging.Formatter):
    def format(self, record):
        return json.dumps({
            "timestamp": self.formatTime(record),
            "level": record.levelname,
            "logger": record.name,
            "message": record.getMessage(),
        })

Context Logging​

Add context to all logs:

import logging

logger = logging.getLogger(__name__)

# Add context to logger
logger = logging.LoggerAdapter(logger, {"request_id": "abc123"})
logger.info("Processing request")
# Output: Processing request [request_id=abc123]