logfire-setup 0.1.0

Interactive CLI to set up Pydantic Logfire with optional dependencies

logfire-setup

Interactive CLI to set up Pydantic Logfire with optional dependencies.

What is this?

logfire-setup is a CLI tool that helps you quickly add Logfire to your Python project with an interactive setup process similar to create-next-app. It:

• Interactive selection with arrow keys and checkboxes for an intuitive user experience
• Checks authentication - Validates your Logfire credentials automatically
• Project selection - Fetches your projects and runs logfire projects use to configure your project
• Auto-detects your existing dependencies (FastAPI, Django, SQLAlchemy, etc.)
• Pre-selects matching Logfire integrations
• Installs Logfire with your chosen extras using uv
• Validates environment - Checks for LOGFIRE_TOKEN and MCP configuration
• Generates best practices documentation for your AGENTS.md or CLAUDE.md

Installation & Usage

Run directly with uvx (no installation needed):

uvx logfire-setup

Or install globally:

uv tool install logfire-setup
logfire-setup

Features

1. Authentication & Project Setup

Automatically checks if you're authenticated with Logfire by validating ~/.logfire/default.toml. If authenticated, fetches your projects, lets you select one, and runs logfire projects use to create .logfire/logfire_credentials.json in your project.

2. Automatic Dependency Detection

The CLI scans your pyproject.toml or requirements.txt to detect existing packages and pre-selects relevant Logfire integrations.

3. Interactive Integration Selection

Choose from two organized sections using arrow keys and spacebar:

Recommended Integrations:

• HTTPX, FastAPI, Pydantic AI, SQLAlchemy

Other Integrations (alphabetically sorted):

• Web Frameworks: Django, Flask, Starlette, ASGI, WSGI
• HTTP Clients: Requests, aiohttp
• Databases: PostgreSQL (asyncpg/psycopg/psycopg2), MySQL, SQLite3, Redis, MongoDB
• Task Queues: Celery
• Cloud: AWS Lambda
• LLM & AI: Google GenAI, LiteLLM
• Monitoring: System Metrics

Detected integrations are pre-selected with checkmarks.

4. One-Command Installation

Automatically runs:

uv add logfire[fastapi,sqlalchemy,redis]

5. Environment Validation

After installation, checks for:

• LOGFIRE_TOKEN environment variable or .env file
• MCP (Model Context Protocol) configuration for IDE integrations (Cursor, Claude Desktop, etc.)

Provides helpful links to create tokens and example configurations if missing.

6. AI Assistant Instructions

Generates custom Logfire best practices for AGENTS.md or CLAUDE.md:

• Core patterns (spans, structured logging, exception handling)
• Integration-specific setup based on your selections
• MCP usage instructions (if configured)
• Security and performance tips
• Direct links to documentation

The instructions are tailored to your selected integrations and displayed inline for review before adding.

Requirements

• Python 3.9+
• uv package manager

Development

Clone the repository:

git clone https://github.com/pydantic/logfire-setup.git
cd logfire-setup

Install dependencies:

uv sync

Run locally:

uv run logfire-setup

Test with uvx:

uvx --from . logfire-setup

License

MIT - see LICENSE for details.

Links

• Pydantic Logfire Documentation
• Logfire GitHub Repository
• uv Documentation