Sam Morrow is a senior software engineer at GitHub leading development of the GitHub MCP Server, open-source infrastructure that connects AI agents to repositories, issues, pull requests, and other developer tools. His work on GitHub Copilot’s agent services and the Model Context Protocol addresses a central challenge of useful autonomy: giving agents powerful capabilities without overwhelming their context windows, exposing sensitive information, or surrendering human control.
A former professional drummer, Morrow began his software career at the BBC in Belfast, building internal tools, quiz-show applications, and web experiences. At IntelliSense.io in Cambridge, he worked on industrial data systems, machine learning, real-time analytics, and Kubernetes infrastructure spanning cloud and on-premises environments.
He subsequently spent four years as a senior software engineer at Jump, developing its jobs platform across Django, React, analytics, and search. He joined GitHub in 2021, initially working on code-scanning security before moving into Copilot Agent Services and leading its official MCP server.
Building agents that know their limits
Progressive tool discovery: Loading every available tool simultaneously consumes context and degrades agent performance. Morrow favors configurable toolsets, permission-aware filtering, deferred loading, and semantic discovery. His writing on progressive discovery places much of the responsibility on how agent clients expose tools, not on MCP itself.
Execution models matched to the task: Structured skills suit procedural workflows; command-line access supports investigation; sandboxed execution enables aggregation while keeping intermediate data outside the context window. His comparative experiments treat these approaches as complementary, without claiming a universal winner.
Authorization that preserves user control: Morrow supports OAuth, PKCE, permission-filtered tool inventories, and incremental authorization that requests additional access only when necessary. His MCP tool-resolution proposal explores exposing permissions, side effects, and execution requirements before invocation.
Security boundaries and human accountability: Morrow treats prompt injection and data exfiltration as ecosystem-wide consequences of combining untrusted content, private information, and externally consequential tools. His trust-and-sensitivity proposal addresses information boundaries, while reviewable AI-generated GitHub issues preserve human-in-the-loop workflows. His AI Engineer Europe presentation also details intent-oriented tool design and stateless server architecture.
Beyond GitHub, Morrow maintains a reMarkable MCP server for tablet documents and highlights, alongside a Python MCP starter for developers building their own servers.
GitHub’s MCP server gained tools faster than agents could use them well. Its evolution shows how defaults, authorization, and request-level architecture shape reliable agent workflows.