Skip to main content
Glama

Twitter User Tweets

twitter_user_tweets
Read-only

Get the tweets a Twitter/X user posted, by username. Returns tweet text, engagement metrics and metadata. Use twitter_user_replies for their replies. Billed $0.006 per page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pagesNoNumber of pages to fetch, 1-20 (default: 1)
usernameYesTwitter username (without @, max 50 characters)
get_sentimentNoAdd AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small surcharge per page, or per request on single-request endpoints.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / get_sentiment / description
      Previous value: -"Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small per-page surcharge."New value: +"Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small surcharge per page, or per request on single-request endpoints."
  2. Changed1 schema field changed
    • changedInput schema / properties / pages / description
      Previous value: -"Number of pages to fetch, 1-10 (default: 1)"New value: +"Number of pages to fetch, 1-20 (default: 1)"
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds value beyond that by describing the return payload (tweet text, engagement metrics, metadata) and disclosing the $0.006 per-page billing, which is real operational context an agent cannot get from the annotations.

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?

Three tight sentences, front-loaded with the core action, followed by return contents, sibling routing and cost. Every sentence carries distinct information with no filler.

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?

With no output schema, the description compensates by naming the returned fields, and it discloses pricing and the reply-tool alternative. It leaves pagination/rate behavior to the schema, so it is complete enough without being exhaustive.

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?

Schema description coverage is 100%, so all three parameters (username, pages, get_sentiment) are already fully documented in the schema, including the surcharge note on get_sentiment. The description confirms username-based lookup but adds no syntax or format detail beyond the schema, so baseline 3 applies.

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?

States a specific verb and resource ('Get the tweets a Twitter/X user posted, by username') and immediately names the sibling it is not (twitter_user_replies), so an agent can disambiguate from the replies tool without opening either schema.

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

Usage Guidelines4/5

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

Explicitly routes the agent to twitter_user_replies when replies are wanted, which is clear context for the main sibling. It does not address when to prefer this over search_twitter or twitter_tweet_details, so it stops short of full when/when-not coverage.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources