AI Tools

PDF to Clean Text for LLM

Extract clean text from PDFs with OpenDataLoader for summarization, translation, embedding, and other LLM workflows

file· File 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/pdf-to-clean-text-for-llm' \
  -F 'file=@/path/to/pdfFile.ext'

# 2) Call the tool with the returned filePath values
curl -X POST 'https://api.elysiatools.com/en/api/tools/pdf-to-clean-text-for-llm' \
  -F 'pdfFile=/public/samples/pdf/financial-report-example1.pdf' \
  -F 'keepLineBreaks=false' \
  -F 'includeHeaderFooter=false' \
  -F 'useStructTree=true' \
  -F 'sanitizeSensitiveData=true' \
  -F 'includePageSeparators=false' \
  -F 'pages='

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/pdf-to-clean-text-for-llm

Parameters

Name	Type	Required	Description
pdfFile	fileupload required	Yes	—
keepLineBreaks	checkbox	No	—
includeHeaderFooter	checkbox	No	—
useStructTree	checkbox	No	—
sanitizeSensitiveData	checkbox	No	—
includePageSeparators	checkbox	No	—
pages	text	No	—

File-type parameters must be uploaded first via POST /upload/pdf-to-clean-text-for-llm, then the returned filePath is passed to the corresponding file field.

Response format

File result

JSON

{
  "filePath": "/public/processing/randomid.ext",
  "fileName": "output.ext",
  "contentType": "application/octet-stream",
  "size": 1024,
  "metadata": {
    "key": "value"
  },
  "error": "Error message (optional)",
  "message": "Notification message (optional)"
}

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-pdf-to-clean-text-for-llm": {
      "name": "pdf-to-clean-text-for-llm",
      "description": "Extract clean text from PDFs with OpenDataLoader for summarization, translation, embedding, and other LLM workflows",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=pdf-to-clean-text-for-llm",
      "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": "pdf-to-clean-text-for-llm",
    "arguments": {
  "pdfFile": "/public/samples/pdf/financial-report-example1.pdf",
  "keepLineBreaks": false,
  "includeHeaderFooter": false,
  "useStructTree": true,
  "sanitizeSensitiveData": true,
  "includePageSeparators": false,
  "pages": ""
}
  }
}

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]