Let AI agents manage OctoPerf load tests, runs, and metrics.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.OctoPerf/octoperf" MCP server from askskill: Run: claude mcp add --transport http 'io-github-octoperf-octoperf' 'https://api.octoperf.com/mcp'
Using OctoPerf, import this API collection, create a load test scenario with 200 concurrent users for 10 minutes, validate the configuration, and run it immediately.
Details of the created and executed load test scenario, including validation and run results.
Find the OctoPerf scenario named "Login API Load Test", increase concurrency from 50 to 150, check for configuration errors, and save the changes.
The updated scenario parameters, validation results, and save status.
Read the key metrics from the latest OctoPerf load test, including response time, throughput, error rate, and peak concurrency, then summarize whether there are performance bottlenecks.
A summary of core performance metrics with a brief assessment of potential bottlenecks.
Measure real-browser web performance to find loading and interaction bottlenecks.
Enable AI agents to automate real-world tasks across APIs, browsers, and systems.
Control remote machine fleets with AI for commands, files, Git, and ops.
Safely let your AI run code, query databases, use LMs, and commit to GitHub.
Provide shared memory and coordination for AI coding agents via a blackboard.
Use AI to test APIs, inspect responses, and troubleshoot issues faster.