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Bio, Work & Ideas

Sam Morrow

Conference affiliation: GitHub · 2026

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.

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Key ideas

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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.

  • More GitHub coverage, worse agent behavior
    0:33 ↗
  • Configuration loses to defaults
    3:11 ↗
  • Reduce what loads and what comes back
    5:06 ↗
  • Make tools express intent, then test their competition
    6:41 ↗
  • Make secure authentication the easy path
    8:14 ↗
  • Secure credentials do not solve prompt injection
    10:45 ↗
  • Let authorization shape the tool list
    12:26 ↗
  • Build a server instance for each request
    13:47 ↗
  • Review the issue before it becomes your contribution
    15:13 ↗
  • From choosing tools to composing them
    16:30 ↗
  • Growing traffic, and one experiment to try
    18:06 ↗

References