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Twitter Search Posts

social_twitter_search_posts
Read-only

Finds public X/Twitter post URLs through Google Search, then returns their details using the same public post scraper as /v1/twitter/tweet. This is Google-indexed discovery, not native X search: coverage is incomplete, recent posts can be missing, and results are ranked by Google rather than newest first. Deleted, protected, or inaccessible posts are omitted. Each post uses the existing tweet response fields, including rest_id, legacy.full_text, legacy.created_at, engagement counts, author and media when available, plus a canonical url. Pass the returned cursor for the next Google page; cursors range from 1 through 11 and null means pagination has ended. The same post may appear on different pages. Each successful page costs 1 credit, including empty results; validation errors and upstream failures are not charged. Replaying cursor=null is uncharged. Allow at least 30 seconds for your client timeout. Completed lookups cost at least 10 Nexscope credits. Actual cost depends on the operation and requested options. Repeated requests may purchase data again. Twitter Search Posts API View Pricing Search public X/Twitter posts by keyword using Google-indexed results, then fetch the post details without a logged-in X account. 1 credit per request Finds public X/Twitter post URLs through Google Search, then returns their details using the same public post scraper as /v1/twitter/tweet. This is Google-indexed discovery, not native X search: coverage is incomplete, recent posts can be missing, and results are ranked by Google rather than newest first. Deleted, protected, or inaccessible posts are omitted. Each post uses the existing tweet response fields, including rest_id, legacy.full_text, legacy.created_at, engagement counts, author and media when available, plus a canonical url. Pass the returned cursor for the next Google page; cursors range from 1 through 11 and null means pagination has ended. The same post may appear on different pages. Each successful page costs 1 credit, including empty results; validation errors and upstream failures are not charged. Replaying cursor=null is uncharged. Allow at least 30 seconds for your client timeout.

Input Schema

NameRequiredDescriptionDefault
queryYesKeyword or phrase to search for in Google-indexed public X/Twitter posts
cursorNoPass the cursor returned by the previous response. Supported page cursors are 1 through 11. A null response cursor means there are no more pages.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond the readOnly/openWorld annotations: it discloses credit costs per page including empty results, that validation/upstream errors are free, that replaying cursor=null is uncharged, that duplicate posts may repeat across pages, and that clients should allow 30s timeouts. This is exactly the operational context an agent needs.

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

Conciseness3/5

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

The core content is well front-loaded, but the description contains a duplicated block (the full paragraph repeats verbatim after the 'Twitter Search Posts API View Pricing' fragment, plus a stray '1 credit per request'), which wastes space and muddies the structure.

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

Completeness5/5

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

With no output schema, the description still enumerates the returned fields (rest_id, legacy.full_text, legacy.created_at, engagement counts, author, media, canonical url), so an agent knows what it will get and how to paginate and budget credits.

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 coverage is already 100%, but the description adds real meaning: cursors run 1 through 11, null means pagination has ended, and replaying null is not charged. It reinforces rather than restates the schema.

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 ('finds public X/Twitter post URLs through Google Search, then returns their details') and explicitly distinguishes itself from native X search, so an agent knows exactly what it retrieves and how it differs from the tweet/profile siblings.

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?

Gives clear selection context by framing this as Google-indexed discovery with incomplete coverage and Google ranking rather than recency, which tells the agent when this tool is appropriate versus native search. It stops short of naming a specific sibling tool to use instead.

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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