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Twitter241 MCP Server

Twitter241 MCP Server

by BACH-AI-Tools
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_tweet_details

Fetch tweet details by providing its ID. Retrieve content, author, metrics, and timestamps for any tweet.

Instructions

Get Tweet Details By Tweet ID

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "pid": "<pid>"
    },
    "name": "get_tweet_details"
  }
}

Input Schema

NameRequiredDescriptionDefault
pidYesExample value: 1631781099415257088

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Get', which implies a read operation, but offers no details about rate limits, authentication requirements, what specific fields are returned, or any edge cases. This is minimal transparency for a tool that presumably accesses external data.

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 a single concise sentence, 'Get Tweet Details By Tweet ID', front-loaded with the verb and object. Every word earns its place, with no filler or redundant phrasing. It is highly efficient.

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

Completeness3/5

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

The tool is simple with one parameter and no output schema, but the existence of sibling tools with very similar names ('get_tweet_details_v2', 'get_tweets_details_by_ids') creates a need for contextual distinction that the description fails to provide. It also omits any indication of response structure or limitations. For a straightforward getter, this is minimally viable but incomplete.

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 full coverage (100%) for the single parameter 'pid' with an example value, so the schema already explains the parameter. The description only restates 'By Tweet ID' without adding additional meaning or context, so it adds no value beyond the schema. Baseline score of 3 applies here.

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

Purpose4/5

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

The description 'Get Tweet Details By Tweet ID' uses a specific verb ('Get') and identifies the resource ('Tweet Details') and the identifier type ('Tweet ID'). It clearly states the tool's function, but it does not differentiate from the sibling tool 'get_tweet_details_v2' or 'get_tweets_details_by_ids', so it lacks distinguishing context.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool instead of alternatives. It does not mention any exclusions, prerequisites, or compare to the similar sibling tools like 'get_tweet_details_v2' or the plural 'get_tweets_details_by_ids'. This absence leaves the agent guessing about selection criteria.

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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