Bring Llm Tracing
to OpenAI Agents SDK

Connect your Langfuse account to any AI agent and take full control of your LLM observability, prompt management, and quality evaluation through natural conversation.

What you can do

• Trace Orchestration — List and retrieve detailed traces of LLM API sessions, exposing latencies, token counts, and exact chained payloads directly from your agent
• Prompt Vault Access — Query actively managed prompt templates and versions to inspect system instructions and expected input variables
• Observation Analysis — Deep-dive into individual spans, events, and generations within a trace to pinpoint failures or performance bottlenecks securely
• Evaluation & Scoring — Attach structured human feedback or automated evaluation metrics to specific traces to monitor model grounding and accuracy
• Usage Metrics — Generate aggregated daily reports on USD costs and average latency to track your AI infrastructure spending in real-time
• Session Monitoring — Extract correlated user sessions to understand multi-turn interaction boundaries and improve long-term agentic workflows

How it works

1. Subscribe to this server
2. Enter your Langfuse API URL, Public Key, and Secret Key
3. Start monitoring your LLM application from Claude, Cursor, or any MCP-compatible client

Who is this for?

• LLM Engineers — debug complex AI chains and measure exact token latencies through natural conversation without manual dashboard searching
• Product Owners — monitor daily AI costs and user satisfaction scores across multiple production environments
• Data Scientists — manage prompt templates and audit evaluation metrics to improve model response quality and grounding efficiently