List courses in the authenticated community. status=published returns only courses visible to learners. Returns id, title, visibility, is_published, thumbnail_url, timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Page size, default 20 | |
| offset | No | Rows to skip, default 0 | |
| status | No | Defaults to "all" |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It transparently lists the returned fields and explains the status parameter's behavioral implications (published = visible to learners), which is valuable. It does not mention pagination behavior or error handling, but the schema covers the parameters and the read-only nature is implied by 'List'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, with the main action front-loaded. It includes the most important filter behavior and return fields without any filler or redundant content, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema and annotations, the description covers the key return fields, the authentication scope, and the behavioral significance of the status filter. For a straightforward list operation, this is sufficient for an agent to understand what the tool does and what to expect, with only minor omissions like sorting or error scenarios that are not critical for selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully describes all three parameters, so the baseline is 3. The description adds semantic value by explaining that status=published returns only courses visible to learners, which enriches the enum meaning. It also indicates the return fields, which provides additional context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists courses in the authenticated community, with a specific verb ('List') and resource ('courses'). It distinguishes from sibling tools like get_course (single course) and create_course by implying a collection operation. The status clarification adds specificity to the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (listing courses) and explains the status=published filter's effect on learner visibility, guiding selection. However, it does not explicitly mention alternatives like get_course for single-course retrieval or exclusions, so it falls short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool targets a distinct resource/action combination, and similar-looking tools are carefully differentiated in descriptions (e.g., get_course_structure vs list_course_modules, update_lesson vs update_lesson_content). There is no meaningful overlap or ambiguity between tools.
All tools use a consistent 'hivelearn_<verb>_<noun>' pattern with common verbs (get, list, create, update). The only minor deviation is 'add' vs 'create' (add_track_course vs create_track), but this is semantically appropriate and does not disrupt the overall pattern.
With 57 tools, the server is significantly over the recommended range and exceeds the 25+ threshold for 'too many'. While the broad domain (courses, community, analytics) justifies a large surface, this many tools makes selection overwhelming for agents and suggests a need for consolidation or sub-servers.
The tool surface covers create, read, and update for most core entities (courses, lessons, quizzes, tracks, posts, events, resources), plus publishing/verification and analytics. However, there are notable gaps: no delete operations for courses, lessons, modules, quizzes, posts, events, resources, or enrollments, and no way to remove a course from a track. These lifecycle holes are significant but not fatal for common workflows.
