logfire — Agent Skill

logfire

Add Logfire observability to Python applications.

Features

• /logfire:connect - connect Claude's MCP client and optionally set up native session telemetry
• /logfire:status - check MCP access, native telemetry configuration, and delivery evidence separately
• /logfire:disconnect - stop native Claude telemetry while keeping MCP and skills
• logfire-coding-agents skill - configure Claude/Codex recording or coding-agent Gateway routing
• logfire-frontend skill - set up browser errors, Web Vitals, and session replays
• logfire-gateway skill - route application model calls through Pydantic AI Gateway
• /instrument - detect frameworks and add Logfire instrumentation
• logfire-setup skill - authenticate, inspect the repository, and route to the right setup workflow
• logfire-infrastructure skill - monitor hosts, containers, Kubernetes, databases, and cloud infrastructure
• logfire-evals skill - add dataset-based evaluations for AI and agent behavior
• /debug - investigate errors using Logfire traces via MCP
• /query - query traces, logs, and metrics interactively or add query capabilities to code
• logfire-ui skill - open Logfire project pages, live views, traces, and Explore filters directly in Codex
• SKILL.md with core Logfire patterns (configure, instrument, structured logging, AI/LLM instrumentation)
• MCP server for querying Logfire data

Query vs UI Routing

The Codex Logfire plugin uses one primary workflow per request:

| User intent | Route | | --- | --- | | Analyze, query, count, summarize, compare, or find root cause | Use logfire-query and return analysis in chat. | | Open, show in browser, live view, Explore, Logfire UI, or give a link | Use logfire-ui and open or return a Logfire URL without querying first. | | Ambiguous prompts like "show recent errors" or "view logs" | Ask whether the user wants a UI view or query analysis. | | Explicit combined prompts like "analyze this and give me a link" | Do the requested query work, then provide the relevant Logfire link. |

For UI requests that omit the organization/project, the agent should resolve the current project through Logfire MCP auth/current-project metadata before asking the user. Environment values such as LOGFIRE_BASE_URL, LOGFIRE_URL, and exporter config identify the platform/API base only; they are not enough to infer the target organization/project.

Install In Claude Code

claude plugin marketplace add pydantic/skills
claude plugin install logfire@pydantic-skills

The Claude plugin provides /instrument, /debug, /query, and the Logfire MCP server.

Connect once

Run /logfire:connect inside Claude Code. It guides you through MCP OAuth and, if you choose, native Claude session telemetry. MCP-only use needs no Logfire CLI. For telemetry, the command locates its managed CLI or offers to install one into a private, persistent uv tool environment; you do not need to run CLI setup commands yourself. Python 3 and uv are needed for that managed install.

Native traces/tool-output capture requires logfire-cli>=0.1.14,<0.2 (the release containing logfire-cli#288). The managed installation uses the package's logfire-cli executable, not the Python SDK's logfire command. Older versions are rejected; MCP and existing skills remain usable independently.