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mcp-twitterio

mcp-twitterio

by fuhaooo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_tweets_by_ids

Fetch tweets by their IDs to retrieve complete tweet data for analysis or integration.

Instructions

通过推文ID获取推文

Args:
    tweet_ids: 推文ID列表，多个ID用逗号分隔，例如"1846987139428634858,1866332309399781537"

Returns:
    包含推文列表的字典

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": {
      "tweet_ids": "<tweet_ids>"
    },
    "name": "get_tweets_by_ids"
  }
}

Input Schema

NameRequiredDescriptionDefault
tweet_idsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior2/5

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 only states the return type ('a dictionary containing a list of tweets') but gives no information on error handling, rate limits, invalid ID behavior, or pagination. This is a minimal disclosure.

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 compact, structured with Args/Returns sections, and every sentence is useful. The purpose statement is front-loaded and the parameter example is directly relevant.

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?

For a simple one-parameter tool with no output schema, the description is adequate but not complete. It lacks context on edge cases (e.g., what happens if an ID is invalid or not found, maximum number of IDs allowed) and doesn't elaborate on the returned tweet structure, which would help an agent fully understand the tool's behavior.

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 0%, so the description compensates by explaining the tweet_ids parameter format: 'list of tweet IDs, multiple IDs separated by commas' with a concrete example. This goes beyond the schema's bare string type and gives the agent actionable syntax guidance.

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 tool's verb and resource: '通过推文ID获取推文' (get tweets by tweet IDs). This distinguishes it from sibling tools like get_user_last_tweets or get_tweet_replies, which focus on user-specific or relation-specific fetches.

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?

The description implies when to use this tool (when you have tweet IDs and need the corresponding tweets) and provides an example argument format. However, it doesn't explicitly exclude alternatives or state edge cases like 'do not use for user timelines', though the purpose is clear enough to infer.

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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