WSUG: Web Services User Group at Drexel University
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Please feel free to join and collaborate with our Web Service User Group (WSUG) members on our Google Group.

Professor, Author, Machine Learning Researcher, Educational Consultant, and Scholar of Teaching and Learning; Host: digitalsignature.fm
less than 1 minute read
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Please feel free to join and collaborate with our Web Service User Group (WSUG) members on our Google Group.
40 minute read
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I now run nine coding agents side by side on a small always-on Ubuntu server: Claude Code, Codex, Antigravity, Grok Build, Hermes, GitHub Copilot, two separate copies of OpenCode, and pi. Herdr keeps them organized, one labelled tab per agent, and brings them back after a reboot. Most of them share one mcpproxy instance for tools. One of those tools talks to a service that needs a personal API key, and only one agent ever holds that key: a deliberately fenced-in OpenCode. The other agents can see the tool, but they can’t authenticate to the service behind it. When they need that service, they hand the task to that OpenCode through Herdr.
5 minute read
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The Model Context Protocol defines a standard way for AI clients to discover and call tools, but standing up a personal MCP server still usually means writing Python glue code, wiring up a framework, and restarting a process every time you add a tool. mcpproxy takes a different approach: every tool provider is a single YAML file, the server reloads tools at startup without any code changes to the host, and a browser-based web UI handles the full provider lifecycle — editing, secret management, and live command streaming — without leaving the browser.
11 minute read
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Most large language model interfaces are designed for developers or for a general consumer audience. Faculty who want to use an AI assistant to help with grading, research, or course preparation either accept the limitations of a consumer chat interface or invest significant time learning to run and configure a developer-grade setup. BetterWebUI is an attempt to close that gap. It is a local Python/FastAPI server with a pure-HTML front end that connects to an existing OpenWebUI instance and layers on the features that make an agentic assistant genuinely useful in a higher-education context: workspaces, skills, MCP server management, CLI shortcuts, math rendering, and a suite of integrations with sibling agentic services.
9 minute read
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Most LLM agents can read files, call APIs, and run shell commands, but they have no reliable way to operate a graphical desktop. They cannot click a button in a running application, verify that a dialog appeared, fill a form field, or observe what is currently on screen. AutoGUI is a research prototype that fills that gap. It connects any OpenAI-compatible LLM — including models served locally through OpenWebUI or directly through Ollama — to a full suite of OS-level desktop controls via a ReAct-style agentic loop.