Text Processing

AI Markdown Article Translator

Translate full Markdown articles with AI while preserving headings, tables, links, images, and code blocks for direct publication

stream· Stream resultOpen tool

Quick start

Call this tool from your code in three languages.

cURL

# 1) Upload each file first → returns { filePath }
curl -X POST 'https://api.elysiatools.com/upload/ai-markdown-article-translator' \
  -F 'file=@/path/to/markdownFile.ext'

# 2) Call the tool with the returned filePath values
curl -X POST 'https://api.elysiatools.com/en/api/tools/ai-markdown-article-translator' \
  -F 'markdownInput=# 发布说明

欢迎使用新版本。

| 项目 | 状态 |
| --- | --- |
| API | 已上线 |

请运行 `npm run build`。

[查看 API 章节](#api-reference)' \
  -F 'markdownFile=' \
  -F 'sourceLanguage=auto' \
  -F 'targetLanguage=english' \
  -F 'glossary=已上线 => live
发布说明 => Release Notes' \
  -F 'preserveAnchorSlugs=true'

API reference

Send a POST request with your inputs as JSON. File parameters require a separate upload first.

Endpoint

HTTP

POST https://api.elysiatools.com/en/api/tools/ai-markdown-article-translator

Parameters

Name	Type	Required	Description
markdownInput	textarea	No	—
markdownFile	fileupload required	No	—
sourceLanguage	select	No	—
targetLanguage	select	No	—
glossary	textarea	No	—
preserveAnchorSlugs	checkbox	No	—

File-type parameters must be uploaded first via POST /upload/ai-markdown-article-translator, then the returned filePath is passed to the corresponding file field.

Response format

Stream result

JSON

data: {"chunk": "data: processed content 1", "type": "stream"}

data: {"chunk": "data: processed content 2", "type": "stream"}

data: {"type": "done"}

MCP integration

Add this tool to your Model Context Protocol server so AI agents can list and call it.

Server configuration

Add this block to your MCP client configuration:

mcp.json

{
  "mcpServers": {
    "elysiatools-ai-markdown-article-translator": {
      "name": "ai-markdown-article-translator",
      "description": "Translate full Markdown articles with AI while preserving headings, tables, links, images, and code blocks for direct publication",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=ai-markdown-article-translator",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

List available tools

After connecting to the SSE endpoint, list the exposed tools:

tools/list

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list"
}

Call this tool

Invoke the tool by its id, passing arguments built from its parameters:

tools/call

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "ai-markdown-article-translator",
    "arguments": {
  "markdownInput": "# 发布说明\n\n欢迎使用新版本。\n\n| 项目 | 状态 |\n| --- | --- |\n| API | 已上线 |\n\n请运行 `npm run build`。\n\n[查看 API 章节](#api-reference)",
  "markdownFile": "",
  "sourceLanguage": "auto",
  "targetLanguage": "english",
  "glossary": "已上线 => live\n发布说明 => Release Notes",
  "preserveAnchorSlugs": true
}
  }
}

Chain multiple tools in one session with a comma-separated toolId list, e.g. /mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp (max 20).

File parameters accept a public file URL only (https://…). Local paths, data: URIs, and Base64 strings are not supported.

Questions or issues? Contact [email protected]