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AI GIF Maker MCP server

AI GIF Maker MCP server

by hanshs474
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Generate an animated GIF

generate_gif

Create animated GIFs from text prompts and return a GIF URL, using native GIF generation instead of video conversion.

Instructions

Turn a text prompt into an animated GIF on AI GIF Maker (aigifmaker.ai) and return the GIF URL. Native GIF generation, no video conversion; usually about a minute. Costs 1 credit on the AI GIF Maker account behind AIGIFMAKER_API_KEY, the same as on the website.

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": "generate_gif"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptYesWhat the GIF should show and how it moves, e.g. "a corgi in sunglasses dancing on a beach, looping".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4/5.0
Behavior4/5

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

With no annotations supplied, the description carries the full burden and does a solid job: it discloses latency ('usually about a minute'), a cost of 1 credit on the account behind AIGIFMAKER_API_KEY, the output (GIF URL), and that generation is native rather than a video conversion. It stops short of stating whether the call blocks for that minute or returns a job handle that must be polled, and says nothing about failure or credit-refund behavior.

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 dense sentences with zero filler, front-loaded with the action and result, then the differentiator, latency, and cost. Every clause delivers information an agent would otherwise have to guess.

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 one-parameter generation tool with no output schema, the definition covers output, latency, cost, and account context, which is most of what a caller needs. The remaining gap is orchestration: given a roughly one-minute runtime and a check_gif sibling, the description should say whether this call is synchronous or requires a follow-up status check.

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?

There is a single required parameter with 100% schema description coverage, so the schema already explains the prompt fully, including an example covering both content and motion. The description adds no prompt-specific guidance (length, style keywords, loop hints) beyond restating that a text prompt drives the result, so baseline 3 applies.

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 ('Turn a text prompt into an animated GIF'), names the platform (AI GIF Maker / aigifmaker.ai), and specifies the return value (GIF URL). The clause 'Native GIF generation, no video conversion' further pins down what kind of generation this is, which an agent can distinguish immediately from the sibling check tools.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: use it when you want a GIF from a text prompt, and the 'no video conversion' note rules out one adjacent use case. However, it never tells the agent when to call check_gif afterwards (polling vs. this call returning a finished result) or when to consult check_credits before spending a credit, even though both siblings exist.

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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