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Trace, evaluate, and optimize LLM, RAG, and agent applications with observability.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "ai.noveum/noveum" MCP server from askskill: Run: claude mcp add --transport http 'ai-noveum-noveum' 'https://noveum.ai/api/mcp'
Developers can use it to trace request flows and inspect key steps when an LLM app becomes slow. It fits teams that need ongoing optimization of inference workflows.
When a team needs to assess a RAG application's performance, it can use the tool for evaluation and observability to spot issues in retrieval or generation. This makes it easier to compare different approaches.
Teams building agent applications can use it to observe execution, identify error-prone or inefficient steps, and optimize accordingly. It is useful for continuously improving multi-step agent workflows.
It provides observability for LLM, RAG, and agent applications, including tracing, evaluation, and optimization. These capabilities help teams understand and improve app behavior.
Based on the description, it is intended for LLM apps, RAG systems, and agent applications. It is relevant if you need to observe execution and outcomes for those systems.
The provided material does not include installation steps, runtime requirements, or API key details; see the source repository. Check the repository documentation for integration specifics as well.
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