Search accounts by username or display_name substring. Returns up to 20 matching users. Use this when the user mentions someone by name (e.g. 'find Jane Smith') and you don't know their username yet. Each result includes the URL-friendly username you can then pass to get_user_profile.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Search query — matches against username and display_name (case-insensitive substring) | |
| limit | No |
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?
The description incorrectly states 'Returns up to 20 matching users' while the schema's limit parameter allows up to 50, creating confusion. It also does not mention pagination, sorting, or empty-result behavior. With no annotations, this misrepresentation is a significant transparency gap.
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?
Three sentences, purposeful and front-loaded; every sentence contributes to purpose, usage, or cross-tool guidance.
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?
The description covers the core use case and result cap but omits the limit parameter's role and returns an inaccurate result limit. Without annotations or an output schema, this leaves gaps for a tool that is otherwise simple.
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 description adds little beyond the schema for q, and it does not explain the limit parameter at all. The 'up to 20' statement actually misleads about limit behavior, and no other parameter semantics are provided.
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 searches accounts by username or display_name substring, and distinguishes it from sibling tools like search_books and get_user_profile by specifying the resource and use case.
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?
It explicitly says 'Use this when the user mentions someone by name... and you don't know their username yet,' and directs the user to pass the resulting username to get_user_profile, making the alternative tool explicit.
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.
Several tools have overlapping purposes. For example, list_my_books and my_books both list authored books, and author_dashboard is a superset; list_orders and my_orders are near-duplicates; check_earnings and payout_balance both report earnings. This creates confusion and risks misselection.
Naming is inconsistent. While many tools use verb_noun (list_annotations, get_book_details), others use my_* (my_books, my_orders), bare nouns (payout_balance), or compound verbs (connect_onboard). The lack of a uniform pattern makes the set feel disjointed.
49 tools is excessive for a server, especially with at least three sets of near-duplicates. The platform is complex, but many tools could be merged (e.g., my_books and list_my_books, list_orders and my_orders). This count will overwhelm agents and increase misselection risk.
The toolset covers the core domain well: discover, purchase, read, comment, review, annotate, publish, monetize, verify, and manage payouts. Minor gaps exist, such as no update/delete annotation, no delete review, and no single-item getter for annotations/reviews, but these are not critical to the main workflows.