Query traces, logs, and metrics in Pydantic Logfire
Logfire is a Observability integration for Agent Serve, the AI workspace where teams build and deploy AI agents. Agent Serve's Logfire integration provides 4 Logfire tools that AI agents can use inside Agent Serve's visual workflow builder. Logfire connects with an API key. Free to start at sim.ai.
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Integrate Pydantic Logfire into workflows. Run SQL over your observability data, search spans and logs with structured filters, pull an entire trace by ID, and confirm which project a read token targets.
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Open your workspace, drag a Logfire block onto the workflow builder, and paste in your Logfire API key.
Pick the tool you need, wire in an AI agent for reasoning or data transformation, and run. Your Logfire automation is live.
Ready-to-use templates featuring Logfire. Click any to build it instantly.
4 Logfire tools available in Agent Serve
Search Records
Search Logfire spans and logs using structured filters for message text, service, span name, severity, environment, and exceptions. Returns the most recent matches first without writing SQL.
Run SQL Query
Run a read-only SQL query against Logfire traces, logs, and metrics. Reads the records and metrics tables using PostgreSQL-compatible syntax.
Get Trace
Fetch every span and log belonging to a Logfire trace, ordered from earliest to latest, so a single request can be reconstructed end to end.
Get Token Info
Resolve which Logfire organization and project a read token belongs to. Useful for confirming a credential targets the expected project before querying it.
Agent Serve's Logfire integration adds 4 Logfire tools to the AI agents you build in Agent Serve's visual workflow builder — you build it all visually. Query traces, logs, and metrics in Pydantic Logfire. Teams often pair Logfire with Sportmonks and Enrich in the same agent.
