get_v1_1_UsersGet Users Group: User. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | No | A comma separated list of User IDs. Up to 100 are allowed in a single request. | |
| usernames | No | A comma separated list of Usernames. Up to 100 are allowed in a single request. |
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?
Annotations are absent, so the description must disclose behavioral aspects. It only mentions billing per call, which is a cost detail, not a behavior like side effects, idempotency, or data scope. It does not state whether this is a read-only operation, what data it returns, or any restrictions. This is severely insufficient transparency.
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?
While the description is very short, it is under-specified rather than concise. The sentence 'Get Users Group: User' is vague and fails to convey meaningful information. The billing note is marginally useful but does not enhance understanding of the tool's function. It represents missing content, not efficient brevity.
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?
With no output schema and only two optional parameters, the description fails to explain what the tool returns (e.g., user objects, fields, formatting) or any response structure. The complexity is moderate, but the description provides no operational context, making it inadequate for an agent to confidently invoke the tool.
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 already provides detailed descriptions for both parameters ('ids' and 'usernames'), including limits and formats, achieving 100% schema coverage. The baseline is 3 since the description adds no parameter information beyond what the schema offers, but it does not need to compensate given the schema richness.
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 says 'Get Users Group: User' which essentially restates the tool name and adds a cryptic 'Group: User' phrase. It does not specify that the tool retrieves user details by IDs or usernames, nor does it distinguish it from sibling tools like get_v2_UserByRestId or get_v1_1_Followers. The purpose is implied from the name but not clearly articulated.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of typical use cases, prerequisites, or conditions under which this should be preferred over other user-fetching tools. The description lacks any contextual direction for the agent.
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 appear to do the same thing, such as get_v1_1_Followers vs get_v2_Followers and get_v2_Tweet vs get_v2_TweetDetail. The descriptions are too brief to clarify differences, and multiple user lookup tools (get_v1_1_Users, get_v2_UserByRestId, etc.) create confusion.
Naming is inconsistent, mixing camelCase (get_ShortUrl), snake_case (get_email_search_by_username), and version prefixes with varying formats (get_v1_1 vs get_v2). No uniform verb_noun pattern is followed.
With 32 tools, the server is overloaded, especially given many redundant variations across API versions. The count exceeds the 25-tool threshold for too many tools, and many could be consolidated.
The server is entirely read-only (all tools are GET), missing write operations like posting tweets, following users, or sending direct messages. This is a significant gap for a Twitter server, and even read coverage has redundancies rather than comprehensive distinct endpoints.