Skip to main content
Glama
scrape-badger

ScrapeBadger MCP Server

Official

search_twitter_tweets

Search Twitter for tweets matching a query. Retrieve tweet text, author details, engagement metrics, and media attachments with support for advanced search operators.

Instructions

Search for tweets by query. Returns matching tweets with text, authors, metrics, and media. Supports advanced Twitter search operators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query string
max_resultsNoMax results (1-100)
Behavior3/5

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

No annotations are provided, so the description carries the burden. It states the return content (text, authors, metrics, media) and supports advanced operators, which is adequate. However, it does not disclose rate limits, authentication needs, or potential limitations like tweet recency, which would improve transparency.

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 with three short sentences that front-load the core purpose and returns. No wasted words, and every sentence adds meaning.

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 tool's simplicity (2 parameters, no output schema), the description is fairly complete: it covers purpose, return types, and advanced operators. It lacks details on pagination or error handling, but these are not critical for a basic search tool with a max_results parameter.

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

Parameters4/5

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

The schema covers 100% of parameters with descriptions, but the tool description adds value by mentioning 'Supports advanced Twitter search operators', giving extra context for the query parameter beyond the schema's 'Search query string'. This justifies a score above baseline 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 verb (search), resource (tweets), and return fields (text, authors, metrics, media). It distinguishes from siblings like get_twitter_tweet (single tweet) and search_twitter_users (users) by specifying tweet-specific search and advanced operators.

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 use for general tweet search by query but does not explicitly guide when to use alternatives like get_twitter_user_tweets or search_twitter_communities. No exclusions or prerequisites are provided, though the tool name and context somewhat compensate.

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/scrape-badger/scrapebadger-mcp'

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