AI agents become useful to developers when they can interact with real tools—but tool access introduces new challenges around permissions, validation, and reliable execution. In this hands-on workshop, participants will build a small agentic developer workflow using the Model Context Protocol (MCP), connecting an LLM to controlled file and Git operations through explicit tool interfaces.

Starting from a prepared repository, we will build a three-stage pipeline that parses a development task, proposes or performs a constrained operation, and validates the result using deterministic checks. Participants will explore local and cloud model configurations, structured tool inputs and outputs, workflow state, and human approval for sensitive actions. The workshop emphasizes reproducible implementation, practical security controls, and a working project that attendees can adapt to their own development workflows.

Key takeaways from the session:

- Implement an MCP server exposing a small set of controlled developer tools.
- Validate tool inputs and outputs using explicit schemas and deterministic checks.
- Coordinate multiple workflow stages while preserving state and error handling.
- Apply permissions, workspace restrictions, and human approval to sensitive operations.