Meet the Workflows: Tool & Infrastructure
Welcome back to our journey through Peli’s Agent Factory!
In our previous post, we explored testing and validation workflows that continuously verify our systems function correctly - running smoke tests, checking documentation across devices, and catching regressions before users notice them. We learned that trust must be verified.
But here’s a question that kept us up at night: what if the infrastructure itself fails? What if MCP servers are misconfigured, tools become unavailable, or agents can’t access the capabilities they need? Testing the application is one thing; monitoring the platform that runs AI agents is another beast entirely. Tool and infrastructure workflows provide meta-monitoring - they watch the watchers, validate configurations, and ensure the invisible plumbing stays functional. Welcome to the layer where we monitor agents monitoring agents monitoring code. Yes, it gets very meta.
Tool & Infrastructure Workflows
Section titled “Tool & Infrastructure Workflows”These agents monitor and analyze the agentic infrastructure itself:
- MCP Inspector - Validates Model Context Protocol configurations
- GitHub MCP Tools Report - Analyzes available MCP tools
- Agent Performance Analyzer - Meta-orchestrator for agent quality
Infrastructure for AI agents is different from traditional infrastructure - you need to validate that tools are available, properly configured, and actually working. The MCP Inspector checks Model Context Protocol server configurations because a misconfigured MCP server means an agent can’t access the tools it needs. The Agent Performance Analyzer is a meta-orchestrator that monitors all our other agents - looking for performance degradation, cost spikes, and quality issues. We learned that layered observability is crucial: you need monitoring at the infrastructure level (are servers up?), the tool level (can agents access what they need?), and the agent level (are they performing well?).
These workflows provide visibility into the invisible.
Learn More
Section titled “Learn More”- GitHub Agentic Workflows - The technology behind the workflows
- Quick Start - How to write and compile workflows
Next Up: Multi-Phase Improver Workflows
Section titled “Next Up: Multi-Phase Improver Workflows”Most workflows we’ve seen are stateless - they run, complete, and disappear. But what if agents could maintain memory across days?
Continue reading: Multi-Phase Improver Workflows →
This is part 12 of a 16-part series exploring the workflows in Peli’s Agent Factory.