VideoGenerationMCP

by AvivK5498

Overview Schema Source Related Servers Discussions Admin

Python

Local

transliterate_hebrew

Transliterates Hebrew text into Latin characters, making it ready for visual prompts in video generation.

Instructions

Transliterate Hebrew text to Latin (via LMStudio/OpenRouter LLM) for visual prompts.

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": {
      "text": "<text>"
    },
    "name": "transliterate_hebrew"
  }
}

Input Schema

Name	Required	Description	Default
`text`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 7, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It transparently reveals that transliteration is performed via LMStudio/OpenRouter LLM, which is useful context about external dependencies. However, it does not mention potential failure modes, latency, or output formatting.

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 sentence that immediately names the action, source, target, and use case. Every word contributes value, with no redundancy or filler.

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?

Given the tool's simplicity (one parameter, output schema present), the description covers the essential contextual aspects: purpose, input language, output script, and intended application. It does not over-elaborate, and any missing return-format details are likely provided by the output schema.

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 provides zero description for the 'text' parameter, and the description partially compensates by indicating the input should be 'Hebrew text' and output is Latin. This adds meaning beyond a bare string field, but lacks detail on encoding, length limits, or transliteration style.

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 uses the specific verb 'transliterate' with a clear resource ('Hebrew text to Latin'), making the tool's function unambiguous. This distinct purpose differentiates it from all sibling tools, which focus on media generation and asset management.

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 phrase 'for visual prompts' provides a clear use case, implying when to use this tool. It does not explicitly name alternatives or exclusions, but no sibling tool performs transliteration, so the context is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.