I build tools that improve how engineers understand, maintain, and ship software systems.
My work focuses on developer productivity, architecture visibility, and AI-assisted workflows — from static analysis and refactoring DSLs to MCP tooling and code intelligence.
- Developer tooling and CLIs for real-world engineering workflows
- Code intelligence and visualization to make large systems easier to reason about
- AI-native development infrastructure that helps both humans and coding agents deliver safely
A unified software modeling DSL and toolchain that lets teams describe architecture in a single .forge file, then render diagrams, generate docs, and lint architecture.
Ultra-fast code review CLI with rustc-style diagnostics for multiple languages, designed for local and CI usage and readable by both humans and LLM agents.
Creates isolated, sandboxed Docker development environments for AI coding agents with a consistent local/remote developer experience.
Semantic code intelligence MCP server that builds knowledge graphs of codebases to improve AI-assisted code exploration.
Desktop app for developers working across many repositories — scans local filesystem repos and provides a single status dashboard.
Go-based CLI that uses GitHub Copilot to generate detailed Backstage catalog documentation for projects.
Multi-repository code visualization as a 3D city view, enabling structural exploration of large codebases.
Model Context Protocol Server Manager for managing MCP server workflows.
- Primary languages: Rust, Go, TypeScript, JavaScript
- Also worked with: Java, Ruby, C++, Scala, Python
- Domains: static analysis, refactoring systems, architecture modeling, documentation generation, developer UX, CI-aware tooling
- Build practical tools that teams can adopt quickly
- Keep systems observable, automatable, and composable
- Optimize for clarity — in APIs, architecture, and developer workflows
- GitHub: @grahambrooks





