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twitr.sh

by sh.twitr

x_extract

Bulk-export X/Twitter data as downloadable datasets: followers, following, repliers, quoters, reposters, likers, mentions, full threads, list and community members, spaces, or people/tweet search results — 23 extractors. Runs async: you get a claim check immediately and poll a free status URL for the download link. Billed per result.

Guidance: tool selects the extractor (23 options). Provide the matching target: targetTweetId (reply/repost/quote/thread/article/favoriters extractors), targetUsername (follower/following/verified/post/mention/likes/media), targetCommunityId, targetListId, targetSpaceId, or searchQuery (people_search, tweet_search_extractor). resultsLimit is MANDATORY — billed per result (article_extractor bills 5× per result). Runs ASYNC: the response is a claim check {snapshot_id, status_url}; poll status_url (free, SIWX) until status=ready for the download link. Idempotency-Key header is required so retries reuse the same job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesWhich extractor to run.
languageNo
minFavesNo
mediaTypeNo
sinceDateNo
untilDateNo
searchQueryNo
resultsLimitYesMANDATORY: max results extracted, billed per result.
targetListIdNo
verifiedOnlyNo
targetSpaceIdNo
targetTweetIdNo
targetUsernameNo
targetCommunityIdNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses async behavior (claim check, polling status_url), billing per result, and idempotency requirement. However, it does not detail error conditions, rate limits, or what happens on failure, leaving some gaps.

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

Conciseness4/5

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

The description is somewhat long but well-structured with a clear first sentence summarizing the tool, followed by bullet-point-like guidance. It front-loads the core purpose. A slightly more concise presentation of the extractor mappings could improve readability, but overall it earns its length.

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 complexity (14 parameters, 23 extractors, async execution, billing, idempotency), the description covers key aspects: extractor selection, target parameters, mandatory limit, async flow with polling, and idempotency. It lacks output schema details but describes the response shape. Error handling is not addressed, which is a minor gap for a complex tool.

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?

Schema description coverage is only 14%, so the description must compensate. It adds significant value by mapping each extractor to the appropriate target parameter (e.g., targetUsername for follower/following extractors), clarifying resultsLimit as mandatory and billed, and explaining the async response structure. While not all 14 parameters are individually described, the mapping covers the critical ones.

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 it bulk-exports X/Twitter data as downloadable datasets, listing 23 specific extractors. This verb+resource specification differentiates it from sibling tools like x_read or x_write, which serve different purposes.

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

Usage Guidelines5/5

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

The description provides explicit guidance on selecting extractors based on target parameters (e.g., targetTweetId for reply/repost/quote extractors), notes that resultsLimit is mandatory and billed, and explains the async workflow. It also mentions the Idempotency-Key header for retries, offering clear when-to-use context.

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

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TDQS

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (write, read, search, monitor, compose, etc.), but some overlaps exist: x_read includes trending topics while x_radar is dedicated to trends, and x_timeline provides engagement lists that overlap with x_extract's extractors. Descriptions help differentiate them, but an agent might initially confuse the boundary between x_read, x_search, and x_timeline for tweet retrieval.

Naming Consistency4/5

All tool names share the x_ prefix and are single words, but mix verb forms (read, search, write, compose, extract, monitor) with noun forms (draws, radar, inbox, lists, profile, timeline). The convention is predictable and uniformly lowercase, but a fully consistent verb_noun or noun-only pattern would be clearer. Minor deviation: x_communities vs x_community are nearly identical and refer to reading vs managing.

Tool Count5/5

14 tools is well within the ideal 3-15 range and each tool covers a distinct functional area of X/Twitter: reading, writing, searching, monitoring, extracting, composing, community management, etc. The count feels appropriate for the broad scope of the server, neither bloated nor thin.

Completeness5/5

The tool surface covers the major X/Twitter interactions comprehensively: fully capable read (x_read, x_search, x_timeline), write (x_write, x_profile), community and list operations, real-time monitoring, bulk extraction, direct messaging, media, trends, and even AI-assisted composition and giveaways. Obvious gaps are minimal, such as no list creation/management commands, but the core lifecycle of tweets, users, communities, and accounts is well covered.

Resources