Tool Use & Environment Interaction

An agent is only as useful as the tools it can call — and only as safe as the tools it cannot. Learn to scope a tool surface from a task, distinguish read from write, and avoid the most common over-provisioning mistakes.

Tool permissions are the contract between trust and capability. Learn to pair each autonomy level with the right consent gate, allow list and audit trail so an agent can act with the least power that still gets the job done.

Learn the concrete moves to register an MCP server with a host: pick the transport, write the config block, declare arguments and environment, and verify capability negotiation before the agent runs.

GitHub ships an official MCP server in two flavours — a local Docker image and a hosted remote server. Learn how to choose between them, scope authentication, and select the right toolsets so the agent can do its job without becoming a supply-chain risk.

Registries are how teams discover and govern MCP servers at scale. Learn the difference between the public MCP catalog, the GitHub MCP Registry and a private/enterprise registry — and how each one feeds into a host's allow-list pipeline.

An agent's behaviour depends on *where* it runs as much as on *what* it can call. Learn to distinguish workspace, branch, session and tenant scopes — and how to keep secrets, files and side-effects in their correct layer.

Branches are the agent's playground; pull requests are the inspectable artefact a human reviews. Learn the conventions GitHub uses for its Copilot coding agent and how branch protections, draft PRs and required reviewers turn autonomous work into safe, reversible work.

Tool calls fail. Networks blip. Tests go red. Safe execution is the discipline of deciding — before you ship — when to retry, when to roll back and when to stop and ask a human. Learn the policies that keep autonomous agents inside their lane.