---
title: "AI agents for universities: 5 real examples"
canonical: "https://agenticfeats.com/agents-for/universities/"
receipts: 5
shown: 3
page: 1
pages: 1
---

> From Agentic Feats: sourced examples of AI agents at work. Map of the site for agents: https://agenticfeats.com/llms.txt

# AI agents for universities

Agentic Feats lists 5 sourced examples of AI agents used in universities; 3 link the artifact; most common agent: Claude Code (2). The most common job type here is research.

## Feats, newest first

- [NSF project summary drafting](https://agenticfeats.com/c/nsf-project-summary-drafting-cursor.md) (Cursor; Claim; 2026-10-13): The author used Cursor in Agent mode with Claude 3.7 Sonnet and two rules files to draft an NSF Project Summary from two papers. Result: The draft was usable but weaker than accepted NSF summaries; thinking mode helped, though it began hallucinating and misreading the sources.
- [Synthetic AGI attitudes survey study](https://agenticfeats.com/c/synthetic-agi-attitudes-survey-study-manus.md) (Manus; Shown; 2026-10-13): Manus planned a survey study on student attitudes to AGI, wrote a Google Apps Script for the form, simulated 1,000 students, and analyzed the data. Result: From one short prompt, Manus produced a publishable-style report with charts from 1,000 synthetic responses. The data is made up.
- [Canvas LMS tool via MCP](https://agenticfeats.com/c/canvas-lms-tool-via-mcp-claude-code.md) (Claude Code; Shown; 2026-10-13): Claude Code co-developed a Canvas LMS MCP server with an educator who is not a developer, covering courses, grading, analytics, and student data anonymization. Result: A roughly 3,000-line open-source Canvas tool built in four months. It cut a 45-minute weekly student check to a 2-minute conversation with Claude.
- [Receipt processing in Cowork](https://agenticfeats.com/c/receipt-processing-in-cowork-claude-cowork.md) (Claude Cowork; Claim; 2026-10-13): Claude Cowork processed a PDF purchasing card receipt, extracting data and producing a cover sheet for the author's TPS report, running its own Python script. Result: Cowork ran the script, fixed an error itself, and returned finished output files with no terminal or manual dependency setup from the author.
- [Course modernization with agent fleets](https://agenticfeats.com/c/course-modernization-with-agent-fleets-claude-code.md) (Claude Code; Shown; 2026-10-13): Claude Code turned course evaluations into tracked GitHub issues, then ran agents to rebuild assignments, exams and about two dozen slide decks. Result: Roughly two dozen decks were rebuilt into Quarto reveal.js with speaker notes and refresh checklists, and the approach was reused for two more courses.