AgentLens: Observability Tool for Multi-Agent AI Workflows

AgentLens is an observability tool designed for multi-agent AI workflows that combine local and cloud-based models. It addresses the challenge of tracking activities across different providers like Ollama, vLLM, Anthropic, and OpenAI.

Key Features

• Unified tracing across Ollama, vLLM, Anthropic, OpenAI, and other providers
• Cost tracking that includes local compute time converted to estimated cost
• MCP server for querying statistics from inside Claude Code
• CLI interface for quick inline checks with commands like agentlens q stats
• Self-hosted - runs on your machine with data staying local

Deployment and Usage

Deploy using Docker:

docker run -d -p 3100:3100 phoenixaihub/agentlens-collector

Wrap Ollama calls with one line of code:

const { client } = wrapOllama(ollama, { client: lens });

The dashboard displays agent flow, cost breakdowns, and latency by provider.

This tool is particularly useful for developers running mixed AI workflows where some tasks use local models (like Ollama) while others require cloud-based models (like Claude or GPT) for complex reasoning.