Caiyun AI Translate MCP. Process multilingual text lists and detect source languages.
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Caiyun AI Translate / 彩云小译: This MCP Server handles high-precision, multi-language translation and text analysis. You can batch translate large text lists and identify languages across major Asian and Western languages (EN, ZH, JA, KO).
It provides confidence scores for every translation, so you know how reliable the output is. Connect it to your AI client to manage global communication tasks quickly and accurately.
What your AI agents can do
Check caiyun status
Checks the API status of the translation service to confirm it's currently online.
Detect language via auto
Automatically determines the language of a given text string.
Translate en to zh
Translates text from English into Chinese.
Your agent uses the detect_language_via_auto tool to determine what language a piece of text is written in.
The translate_multiple_lines tool processes and translates an entire list of text strings at once.
The translate_text tool sends a list of multiple strings for translation into a target language.
The dedicated tools (e.g., translate_en_to_zh, translate_ja_to_zh) handle direct, high-quality translation between two specified languages.
Use translate_to_en to convert source text into English.
Use translate_to_zh to convert source text into Chinese.
Ask AI about this MCP
Supported MCP Clients
Gemini Waiting for input…
019d8422check caiyun status
Checks the API status of the translation service to confirm it's currently online.
019d8422detect language via auto
Automatically determines the language of a given text string.
019d8422translate en to zh
Translates text from English into Chinese.
019d8422translate ja to zh
Translates text from Japanese into Chinese.
019d8422translate ko to zh
Translates text from Korean into Chinese.
019d8422translate multiple lines
Translates a batch of multiple text blocks simultaneously.
019d8422translate text
Translates a list of multiple text strings into a target language.
019d8422translate to en
Translates any source text into English.
019d8422translate to zh
Translates any source text into Chinese.
019d8422translate zh to en
Translates text from Chinese into English.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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Make Your AI Do More
Start with Caiyun AI Translate / 彩云小译, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
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- Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector
Caiyun AI Translate handles high-precision, multi-language translation and text analysis right through your AI client. It's built for managing global content, letting your agent act like a real-time linguistic coordinator. You'll use it for everything from small social media feeds to massive resource files. Every translation result comes with a confidence score, so you always know how reliable the output is.
You'll also check the service status using check_caiyun_status to make sure it's online before you start.
Your agent first determines the source language using detect_language_via_auto on any text string. You can then translate the content in several ways. If you've got a list of multiple strings, you can send 'em all at once using translate_multiple_lines or the translate_text tool. You'll use translate_to_en to convert any source text into English, or translate_to_zh to convert any source text into Chinese.
For specific language pairs, the dedicated tools handle the job. You can use translate_en_to_zh to translate English into Chinese. You can use translate_ja_to_zh to translate Japanese into Chinese. You can use translate_ko_to_zh to translate Korean into Chinese. You can also translate Chinese back to English using translate_zh_to_en.
How Caiyun AI Translate MCP Works
- 1 First, your agent calls a detection tool like
detect_language_via_autoto confirm the source language. - 2 Next, the agent selects the right translation tool, whether it’s a general call like
translate_textor a specific pair liketranslate_en_to_zh. - 3 The server returns the translated text, plus a confidence score, allowing your agent to pass the data directly into the next step of your workflow.
The bottom line is that your AI client uses the structured tools to execute translations and language checks without needing complex external API management.
Who Is Caiyun AI Translate MCP For?
Content Localization Managers. Tech Writers. Customer Support Engineers. Global Marketing Specialists. If your job involves moving text between English, Japanese, Korean, and Chinese, this is for you. You need to process massive amounts of varied text fast, and the accuracy of the translation matters.
Handles translating thousands of UI strings and resource files for software releases, ensuring consistency across all language pairs.
Creates documentation for global products, using the server to translate technical manuals and usage guides into multiple languages.
Translates customer feedback or chat transcripts from various international regions into a single source language for analysis.
What Changes When You Connect
- Scale text localization. Instead of calling multiple APIs, use
translate_textortranslate_multiple_linesto process hundreds of strings in one call. This cuts down on orchestration complexity. - Maintain data integrity. Every translation result includes a confidence score. You check the score before accepting the text, eliminating guesswork.
- Handle specific pairs efficiently. Need Japanese to Chinese? Use
translate_ja_to_zh. The dedicated tools provide optimized performance for the most common language paths. - Minimize setup steps. Your agent can first run
detect_language_via_autoto figure out the source language, then select the correct translator tool. This removes manual language identification. - Process varied content. The server supports translating both full text lists (
translate_text) and multiple discrete blocks (translate_multiple_lines), handling different data structures. - Centralize translation. Use the dedicated
translate_to_enortranslate_to_zhtools to route content to a specific target language, regardless of the source language.
Real-World Use Cases
Localizing a Mobile App UI
The app team needs to update 500 strings for the next release. They ask their agent to run translate_text on the entire list, targeting French (or any other language supported). The agent gets back the translated list and the confidence score for each string, ready for review.
Analyzing Social Media Feeds
A market analyst gets a feed of mixed-language tweets. They ask their agent to first run detect_language_via_auto on the whole batch. Then, they iterate over the detected languages, running the appropriate translation tool (e.g., translate_ko_to_zh) until all data is standardized in Chinese.
Translating a Technical Document
A technical writer needs to convert a Japanese manual into Chinese. They instruct their agent to run translate_ja_to_zh. The agent handles the entire workflow, ensuring the correct, optimized tool is used, and delivers the final, accurate Chinese text.
Preparing for a Global Launch
A product team has source text in English but needs to validate the Chinese translation. They ask their agent to run translate_en_to_zh and then immediately run translate_zh_to_en on the result. This loop verifies the round-trip accuracy of the translation.
The Tradeoffs
Writing complex logic in the LLM prompt
Asking the AI to 'Translate this text to Chinese, but if it's Japanese, use the Japanese-to-Chinese tool, otherwise use the general translation tool.' This forces the AI to guess the right tool and is unreliable.
→
Let your agent handle the routing. First, call detect_language_via_auto. Then, based on the output, the agent calls the most specific tool, like translate_ja_to_zh. Keep the logic simple and tool-driven.
Treating all translation tools as general
Calling translate_text for every single language pair, even when a dedicated tool like translate_en_to_zh exists. This is inefficient and misses optimized paths.
→
Always check the tool list first. If you know the source and target (e.g., English to Chinese), use the dedicated tool translate_en_to_zh. Only use general tools when the language pair is unknown.
Ignoring API health checks
Running a critical batch job without first checking the connection status, leading to the job failing mid-stream with an unhandled network error.
→
Start every workflow by calling check_caiyun_status. If the status isn't green, don't run the translation. This prevents wasting time and resources.
When It Fits, When It Doesn't
Use this if you need to manage translation across multiple, diverse languages (EN, ZH, JA, KO) and need reliability metrics (confidence scores). The best path is to let your agent manage the workflow: detect_language_via_auto -> (select best specific tool) -> (use translate_multiple_lines for scale).
Don't use this if your translation need is simple, single-pair, and never needs to scale beyond one or two calls. In that case, a simple API wrapper might suffice. Use this when you need the intelligence layer to select the right tool from the available 10 options and handle the full process, from detection to batch translation.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Caiyun AI Translate / 彩云小译. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Dealing with global text means copy-pasting between 5 different APIs.
Right now, localizing content means opening the source file, running it through the English API, downloading the result, opening the Japanese API, and repeating that process for Korean, Chinese, and so on. You end up with a dozen browser tabs, five different credentials, and a ton of manual copy-pasting.
With this MCP server, your agent handles the whole thing. You ask it to translate the source text list, and it routes the data through the correct tools (`translate_text` or `translate_multiple_lines`). You get the final, translated output right in your chat window.
Caiyun AI Translate MCP Server: Translate text lists and detect languages
The biggest time sink is the language identification. You spend time checking if the text is Japanese or Korean before you even start translating. Now, your agent runs `detect_language_via_auto` first. It tells you the language in milliseconds.
It’s done. Your AI client handles the entire translation pipeline—detection, translation, and structured output—in one conversation. You don't touch a single API key or documentation page.
Common Questions About Caiyun AI Translate MCP
How do I check the connection status using the `check_caiyun_status` tool? +
Call check_caiyun_status to confirm the server is up. This is the first step any serious workflow should take. It returns a simple status indicator so you know if you can proceed.
Is `translate_text` the same as `translate_multiple_lines`? +
No. translate_text is for passing a list of discrete strings. translate_multiple_lines is for translating a batch of text blocks that maintain some context. Use both depending on your data format.
What if I only need to go from Chinese to English? +
Use the dedicated tool translate_zh_to_en. This is faster and more optimized than using the general translate_to_en tool for this specific, known pair.
Can I detect the language before I translate? +
Yes. Use detect_language_via_auto first. This tool reads the input and tells you the language, letting you select the correct translation tool next.
What is the best way to translate a mixed-language document? +
Run detect_language_via_auto on the whole document. Then, iterate over the detected language list and call the appropriate dedicated tool (e.g., translate_ja_to_zh) for each section.
What happens if I try to translate a large volume of text using `translate_multiple_lines`? +
The tool handles large volumes efficiently by processing text in batches. You pass the entire list of strings, and the server returns the corresponding translations, maintaining context and speed.
How do I make sure the translation output is accurate for specific language pairs, like Japanese to Chinese, using `translate_ja_to_zh`? +
Use the dedicated translate_ja_to_zh tool for guaranteed precision. This tool is optimized for the Japanese to Chinese pair, ensuring high-quality, context-aware results for that specific linguistic mapping.
Can I use `detect_language_via_auto` to figure out what language a mixed-language document is written in? +
Yes, detect_language_via_auto identifies the primary language of any given text. It gives you the language code, letting your agent figure out the best next step, whether that's translating or passing the data along.
How do I find my Caiyun Interpreter Token? +
Log in to the Caiyun Open Platform, navigate to the API Token section in your dashboard to find your unique Interpreter Token.
What does 'auto2zh' mean? +
It is a direction code where 'auto' indicates automatic source language detection and 'zh' indicates Simplified Chinese as the target language. Other codes follow the [source]2[target] pattern.
Can I translate multiple lines at once? +
Yes! Use the translate_text or translate_multiple_lines tools. You can provide a comma-separated list or a JSON array of strings to be translated in a single API call.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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