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Trace and analyze Langfuse LLM observability data for debugging and optimization.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "com.pulsemcp/langfuse" MCP server from askskill: Run: claude mcp add 'com-pulsemcp-langfuse' -- npx -y langfuse-observability-mcp-server
Connect to Langfuse and find the model call traces with the highest failure rates in the last 24 hours. Group by application and model, list error types, counts, and average latency, then summarize the most likely root causes.
A failure analysis report with high-risk traces, error statistics, latency patterns, and root-cause summary.
Analyze the performance of different prompt versions over the last 7 days. Compare success rate, average response time, token usage, and user ratings, identify the best and worst versions, and provide optimization suggestions.
A prompt version comparison showing rankings and actionable optimization recommendations.
Review this week's Langfuse observability data and identify APIs or workflows with unusually high token usage or inference cost. Explain when the anomaly started, its impact, and possible causes.
A cost anomaly diagnosis summarizing affected items, time trends, and likely optimization opportunities.
Connect Gmail to read, search, and automate email workflows easily.
Inspect Hatchbox env vars, trigger deploys, and monitor Rails processes.
Browse and discover MCP servers from the PulseMCP sub-registry.
Manage Fly.io apps, machines, logs, and Docker images efficiently.
Convert bitmap images into editable SVG vector graphics through automatic tracing.
MCP server for Slack — read/write messages, manage threads, and react to messages.
Access and manage Langfuse prompts through MCP for faster prompt workflows.
Manage Langfuse prompts, observability, and metrics through natural language workflows.
Use natural language to build, manage, and run Langflow workflows.
Connect AI assistants to Langflow to build, manage, and automate workflows.
Monitor dev logs and surface runtime errors for instant AI code verification.
Search Langfuse docs to debug, evaluate, and improve LLM applications.