AUTOMATION
Agent-Driven Browser Performance Tracing with Real-Time Bottleneck Detection
Autonomous browser automation with integrated performance monitoring and aspire trace reporting
Updated: 5/24/2026
Difficulty
hard
Time
2-4 hours
Use Case
Identify and debug performance bottlenecks in web applications using autonomous agents
Popularity
0 views
About this automation
Build an MCP server that enables an AI agent to drive a browser while simultaneously reporting performance traces to aspire, allowing real-time identification of the slowest operations without manual intervention
How to implement
1
Create MCP server with browser control capabilities
2
Integrate aspire trace reporting into the MCP server
3
Configure agent to autonomously navigate and interact with browser
4
Set up real-time trace collection and analysis
5
Implement bottleneck detection logic
6
Create feedback loop for agent to identify slowest operations