Logging, Tracing, and Debugging with Logfire MCP

Hosted by Samuel Colvin

Thu, Sep 4, 2025

6:00 PM UTC (45 minutes)

Virtual (Zoom)

Free to join

Invite your network

Go deeper with a course

Elite AI Assisted Coding
Eleanor Berger and Isaac Flath
View syllabus

What you'll learn

Using Pydantic Logfire

Pydantic Logfire is an observability platform designed to be easy to set up and understand.

Logging, Tracing, and Debugging

How to use Logfire to observe complex systems and find needles in haystacks.

Agentic debugging with Logfire MCP

Using Logfire MCP with your AI agent to integrate observability into your workflow.

Why this topic matters

Unlock powerful AI debugging workflows by connecting your agents directly to observability data. Pydantic Logfire's MCP integration enables LLMs to query traces, metrics, and logs in real-time, transforming how you monitor and troubleshoot AI applications.

You'll learn from

Samuel Colvin

Founder @ Pydantic

I started working on Pydantic out of a mixture of frustration that type hints do nothing at runtime and curiosity as to whether they could be used to validate data.


Turns out I was right (or lucky) and with Pydantic's crazy growth, the maintainers behind it now get to build other products with the same principles — that the most powerful tools can still be easy to use.

Pydantic - Know more. Build faster.

Pydantic

Sign up to join this lesson

By continuing, you agree to Maven's Terms and Privacy Policy.