Log Analyzer MCP

#!/bin/bash # Add known location of user-installed bins to PATH # export PATH="/usr/local/bin:$PATH" # Adjust path as needed - REMOVED set -euo pipefail # Run log_analyzer_mcp_server using Hatch for development # --- Define Project Root --- SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" PROJECT_ROOT="$(cd "${SCRIPT_DIR}/.." && pwd)" # --- Change to Project Root --- cd "$PROJECT_ROOT" # Don't print the working directory change as it will break the MCP server integration here echo "{\"info\": \"Changed working directory to project root: $PROJECT_ROOT\"}" >> logs/run_log_analyzer_mcp_dev.log # Install hatch if not installed if ! command -v hatch &> /dev/null; then echo "{\"warning\": \"Hatch not found. Installing now...\"}" pip install --user hatch # Consider if this is the best approach for your environment fi # Ensure logs directory exists mkdir -p "$PROJECT_ROOT/logs" # --- Set Environment Variables --- export PYTHONUNBUFFERED=1 # export PROJECT_LOG_DIR="$PROJECT_ROOT/logs" # Server should ideally use relative paths or be configurable export MCP_SERVER_LOG_LEVEL="${MCP_SERVER_LOG_LEVEL:-INFO}" # Server code should respect this # --- Run the Server --- echo "{\"info\": \"Starting log_analyzer_mcp_server with PYTHONUNBUFFERED=1 and MCP_SERVER_LOG_LEVEL=$MCP_SERVER_LOG_LEVEL\"}" >> logs/run_log_analyzer_mcp_dev.log # The actual command will depend on how you define the run script in pyproject.toml # Example: exec hatch run dev:start-server # For now, assuming a script named 'start-dev-server' in default env or a 'dev' env echo "{\"info\": \"Executing: hatch run start-dev-server\"}" >> logs/run_log_analyzer_mcp_dev.log exec hatch run start-dev-server