Awesome Reviewers

Configuration must be internally consistent: what you declare in pyproject.toml and document (e.g., env vars) must match what the code actually does, and dependency/tooling choices must align with the project’s toolchain.

Apply this checklist:

• Use realistic, compatible dependency minimums: avoid overly-loose floors that allow ancient API-incompatible releases; avoid version specs with no stable releases.
• Keep tooling dependencies aligned with the chosen workflow (e.g., don’t keep virtualenv if you use uv).
• If you advertise an environment variable (like FASTMCP_LOG_LEVEL), ensure code/config actually reads it and applies it (e.g., configure Loguru at startup).

Example (dependency + logging wiring):

# pyproject.toml
[project]
dependencies = [
  "fastmcp>=2.13.1", # avoid dangerously loose floors
  # ...
]
# If using uv, avoid redundant virtualenv tooling dependencies.

# server.py (startup)
import os
import sys
from loguru import logger

level = os.getenv("FASTMCP_LOG_LEVEL", "INFO")
logger.remove()
logger.add(sys.stderr, level=level)

Net effect: fewer “works in README but not in runtime” surprises and fewer dependency-resolution failures caused by inconsistent configuration.

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