Skip to main content
Glama
DanielTomaro13

sportsdata-mcp

twitter_users

Read-onlyIdempotent

Retrieve Twitter user details by numeric IDs in batches of up to 100. Returns usernames, names, and public metrics for sports data analysis.

Instructions

Batch account lookup by numeric ids (up to 100).

Returns: {data:[{id, username, name, public_metrics}]}

Auth: needs your own key in X_BEARER_TOKEN.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYesNumeric user id(s), up to 100.
user_fieldsNoUser fields (CSV).username,name,public_metrics
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, but the description adds valuable context: the batch limit of 100, the return format, and the required X_BEARER_TOKEN auth. This goes beyond annotations and helps the agent understand operational constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the main purpose, followed by return format and auth details. Every line provides necessary information without fluff, making it highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of an output schema, the description explicitly states the return format and auth requirements, which is good. It covers purpose, limit, and operational details. However, it doesn't mention behavior for invalid or missing IDs, which is a minor gap for a batch lookup tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for both parameters (ids and user_fields), so the schema already provides the necessary semantics. The tool description re-states the 100-id limit but does not add new parameter details beyond the schema, resulting in a baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a batch account lookup by numeric ids with a limit of 100. It specifically names the resource (accounts), the operation (lookup), and the scope (by numeric ids), which distinguishes it from sibling tools like twitter_users_by_usernames.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for numeric ID lookups but does not explicitly mention when to use this tool over alternatives like twitter_user_by_username or twitter_users_by_usernames. It provides a constraint (up to 100 ids) but lacks comparative guidance, so usage context is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DanielTomaro13/sportsdata-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server