CampusMind-AI
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tasks | {
"list": {},
"cancel": {},
"requests": {
"tools": {
"call": {}
}
}
} |
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
| resources | {
"subscribe": true,
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| loginA | Authenticate with email and password. Returns a session token for subsequent requests. |
| list_coursesB | List all courses a student is enrolled in with basic info |
| get_conceptB | Get details about a specific concept including current mastery for a student |
| ask_questionA | Ask a question about a course topic. The system reads memory, answers using course context, identifies relevant concepts, infers confusion from phrasing, logs an interaction, and updates mastery records. |
| explain_conceptA | Get an adaptive explanation of a concept based on your current mastery level. Deeper explanations for weaker topics, concise for stronger ones. |
| log_quiz_resultA | Log a quiz or quick-check result for a concept. Updates mastery: correct answers boost confidence, incorrect ones reduce it and increment the wrong count. |
| log_topicA | Log a topic or doubt a student studied or asked about. Stores it with a timestamp and returns an id. |
| recall_topicA | Search previously logged topics by a keyword or vague query. Performs a fuzzy match against subject, topic, and note from interaction history. |
| get_mastery_heatmapA | Get mastery data organized by course for the mastery heatmap widget. Returns courses with their concepts and confidence scores. |
| get_review_dueA | Proactively find concepts that have not been reviewed in at least N days (spaced-repetition style). Returns overdue concepts with effective confidence and days since review. |
| mark_reviewedA | Mark a concept (by id) as reviewed right now. Resets its review clock, applies a confidence boost, and increments awareness. |
| demo_backdate_topicA | DEMO/TESTING ONLY: artificially age a concept's last-reviewed timestamp by N days so get_review_due can be tested without waiting real time. |
| set_study_goalA | Set a study goal for a student with a deadline. Goals appear in daily briefings and help the planner prioritize. |
| record_study_sessionA | Record a completed study session. Stores which topics were studied and duration, updates study streak analytics. |
| get_daily_briefingA | Build a daily academic summary: what is due soon, what should be reviewed today, trending weak topics, and urgent items. Call this at session start for a proactive briefing. |
| suggest_review_planA | Generate a spaced-repetition review plan from mastery data and recency. Prioritizes weak and long-unreviewed concepts. |
| flag_at_risk_topicsB | Surface concepts where low confidence intersects with deadline pressure or prolonged neglect. Prioritizes topics that need urgent intervention. |
| get_deadline_timelineA | Get deadlines organized for the timeline widget. Returns upcoming assignments sorted by due date with course context. |
| start_voice_sessionA | Creates a new voice interaction session. Logs the start and returns a greeting tailored to the student's current context — recent activity, upcoming assignments, and weak topics. |
| process_voice_inputA | Processes spoken input from a voice session: detects intent from transcript keywords, logs the interaction with voice-specific fields, updates mastery if a learning-related intent is detected, and returns a structured spoken response. |
| end_voice_sessionA | Ends an active voice session, logs a summary interaction, and returns session statistics including duration, interaction count, and topics covered. |
| get_progress_summaryA | Get a progress analytics summary: confidence trends, study hours, completed sessions, and weak areas. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| voice-tutor-session | Instructs the AI for voice-based tutoring using spoken-word style: shorter sentences, clearer phrasing, and a conversational tone optimized for text-to-speech output. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Student Profile | Returns identity and academic profile details for the student |
| Course Syllabus | Returns the full syllabus for a course in markdown |
| Academic Memory Graph | Compact memory snapshot: enrolled courses, concept mastery, recent struggles, and study streak. Load this first when starting a session. |
| Weak Topics | Low-confidence concepts sorted by urgency, most in need of review first |
| Upcoming Deadlines | Near-term deadlines sorted by due date, with course context |
| Health Checks | Current health status of all registered health checks |
| Recall List | UI component for Recall List |
| Mastery Heatmap | UI component for Mastery Heatmap |
| Review Due | UI component for Review Due |
| Deadline Timeline | UI component for Deadline Timeline |
| Progress Dashboard | UI component for Progress Dashboard |
| Widget Examples | Provides metadata and examples for all registered UI widgets |
TDQS
Scored across 22 tools
Most tools target distinct resources and actions, but some overlap exists between get_review_due and suggest_review_plan (both about review scheduling) and between ask_question and explain_concept (both about learning support). Descriptions help clarify boundaries, but an agent might occasionally pick the wrong tool without careful reading.
All tool names follow a consistent verb_noun pattern in snake_case, with verbs like get, list, log, set, start, and end. The naming is uniform and predictable, making it easy to infer functionality from the name.
With 22 tools, the server is on the heavier side of the typical range. While each tool serves a purpose in the learning assistant domain, some consolidation could reduce redundancy (e.g., merging or streamlining review-related tools), making the count feel slightly bloated.
The tool set covers the core learning workflow well: authentication, course viewing, concept mastery, questioning, explanations, quiz logging, study sessions, review scheduling, goals, and voice interaction. Minor gaps exist, such as no way to list or update study goals and no direct way to view all logged topics beyond search, but these are workable.