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OpenTweet MCP Server

OpenTweet MCP Server

Official
by opentweetio
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

opentweet_generate_image

Generate AI images from text prompts using Grok Imagine and get a permanent URL for use in tweets.

Instructions

Generate an AI image from a text prompt using Grok Imagine (xAI). Returns a permanent URL ready to use in tweets via media_urls. Requires XAI_API_KEY to be configured on the server.

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": {
      "prompt": "<prompt>"
    },
    "name": "opentweet_generate_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptYesDescription of the image to generate
resolutionNoImage resolution. Default: 1k
aspect_ratioNoImage aspect ratio. Default: 1:1

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

A4/5.0
Behavior3/5

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

Annotations (openWorldHint, idempotentHint, destructiveHint) are present but vague. The description adds that generation uses Grok Imagine and returns a permanent URL, but doesn't disclose potential side effects like cost, rate limits, or failure modes. Consistent with annotations, but could provide more detail.

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?

Two sentences clearly convey the action, output, and prerequisite. No wasted words, every sentence earns its place.

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?

For a simple 3-parameter tool with no output schema, the description covers input, output, and prerequisite. Missing minor details like default values for optional parameters or rate limits, but is adequate for an agent to use the tool.

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 coverage is 100% with descriptions for all three parameters. The description adds no extra meaning beyond what the schema provides, so baseline of 3 is appropriate.

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 generates an AI image from a text prompt using Grok Imagine and returns a permanent URL for tweets. This distinguishes it from sibling tools like opentweet_upload_media (uploads existing media) and opentweet_generate_video (generates video).

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 mentions the prerequisite (XAI_API_KEY) and that the URL is ready for tweets via media_urls, providing clear context. However, it does not explicitly state when to use this tool over alternatives, though the differentiation is implicit.

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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