The greatest bottleneck in building effective AI agents isn't the model's reasoning capability; it is the integration boundary where the LLM connects to actual developer tools, file systems, and environments. This session delivers a deep-dive technical look at utilizing the Model Context Protocol (MCP) to bridge that gap safely.We will walk through how we implemented MCP tools to expose shell, file, and git capabilities safely within a 7-phase agentic software pipeline. We will explore how to expose orchestrator capabilities directly to VS Code and Claude Desktop workspaces, manage context windows efficiently, and design secure tool interfaces that minimize the risk of destructive actions. This talk features live code demonstrations of functional MCP servers designed for advanced engineering automation.

- Takeaways:
- MCP Infrastructure: Setting up and configuring secure Model Context Protocol servers inside real-world developer environments.
- Secure Tool Design: Writing robust schemas that expose environment capabilities to AI agents without risking pipeline execution.
- Context Window Engineering: Techniques for pruning and filtering data streams to maximize prompt context efficiency.