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Translate across 200+ languages locally with no cloud dependency or cost.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.damoqiongqiu/mcp-local-translate" MCP server from askskill: Run: claude mcp add 'io-github-damoqiongqiu-mcp-local-translate' -- npx -y @damoqiongqiu/mcp-local-translate
Translate the following product description into English, Spanish, and Japanese. Keep the marketing tone and separate each version: "This app helps teams organize customer feedback faster and generate summaries."
Returns English, Spanish, and Japanese translations suitable for product copy.
Translate this English research abstract into Chinese and French, preserving terminology accuracy: "Large-scale multilingual models improve translation quality for low-resource languages."
Provides Chinese and French translations while preserving technical and academic wording.
Translate the following internal notice from German to Chinese locally, without omitting dates, names, or IDs: "Interne Mitteilung: Projektstatus wird am 12. Mai von Anna Weber aktualisiert, Referenz ID-4821."
Returns a complete Chinese translation preserving dates, names, and reference IDs.
Developers, researchers, or content teams can translate text directly on their own machine when content must not be sent to the cloud. It fits internal notices, draft materials, or sensitive document excerpts.
When copy or documentation needs to be expanded into many languages, users can use this tool for translation across 200+ languages without cloud service costs. It is suitable for individuals or small teams with limited budgets.
In environments with limited connectivity or where external services are undesirable, users can still run translation tasks locally. It suits workflows that prioritize control and self-contained operation.
It provides local NLLB-based translation and can translate across more than 200 languages on your machine. The description emphasizes zero cloud usage and zero cost.
Based on the provided description, it runs entirely on your machine and does not depend on cloud services. Whether it needs network access to fetch models or dependencies is not stated; see the source repository.
The provided material does not include installation steps or runtime prerequisites. For setup instructions, model dependencies, and system requirements, see the source repository.
Lets AI directly read and update locale JSON translation files.
Provides localization data for 174 locales to create culturally adapted multilingual content.
Run Llama models locally for private, offline AI assistance.
Translate text and detect languages for fast multilingual content handling.
Transcribe, translate, and synthesize English-Chinese speech from WAV audio files.
Speak text and task summaries offline using native system voices instantly.