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Tapra MCP server

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by tapra-ai
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Translate subtitles

translate_subtitles

Translates SRT or VTT subtitle files between Tunisian Derja and English, French, or Modern Standard Arabic while preserving timings and speaker labels; batches lines to control cost.

Instructions

Translate an SRT or VTT file between Tunisian Derja and English, French, or MSA, keeping every timing and speaker label. Lines are sent in batches to keep cost low. Pair with create_voiceover (srt_path) to dub a video. Reports progress per batch. Costs money per character.

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": {
      "input_path": "<input_path>",
      "target": "<target>"
    },
    "name": "translate_subtitles"
  }
}

Input Schema

NameRequiredDescriptionDefault
formatNosame
sourceNoSource language. Usually auto-detected.
targetYesTarget language, e.g. "French", "English", "Derja", "MSA" (see list_translation_languages).
input_pathYesSRT/VTT file, e.g. from transcribe_video, or a tapra://output/... resource.
output_pathNoWhere to save. Default: <name>.<target>.srt in the output folder.
max_cost_tndNoRefuse to run if the estimated cost is above this many TND. Defaults to TAPRA_MAX_COST_TND when set.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the annotations (which only declare non-read-only, open-world, non-idempotent) by disclosing the cost model (per character, batched to keep cost low), progress reporting per batch, and the guarantee that timings and speaker labels are preserved. These are exactly the traits an agent needs before committing spend.

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?

Five short sentences, each carrying distinct information, front-loaded with the core operation and ending with the cost caveat. No filler or repetition despite covering purpose, formats, batching, chaining and pricing.

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 6-parameter mutating tool with no output schema, the description covers cost, progress, label preservation and downstream chaining well. The remaining gap is that it never says what the call returns (e.g. the output file path) or that source auto-detection is the default, which matters given the absent 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?

Schema coverage is 83%, so the schema already documents input_path, target, source, output_path and max_cost_tnd. The description only reinforces that timing/speaker labels are retained and that language names are bounded; it adds little about format or output_path beyond what the schema states. 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 (translate) plus the exact resource (SRT or VTT subtitle files) and the language pairs (Tunisian Derja to/from English, French, MSA). The file-format restriction cleanly separates it from the plain text `translate` sibling without needing the schema.

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?

Gives concrete usage context: pair with create_voiceover (srt_path) to dub a video, and it warns that the operation costs money per character. It implies this is the choice when the input is a subtitle file, but never explicitly contrasts it with the `translate` sibling or states when not to use it.

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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