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LibreOffice MCP Server - Usage Examples

This document provides practical examples of how to use the LibreOffice MCP Server.

Basic Document Operations

Creating Documents

# Create a Writer document with content
result = create_document(
    path="/path/to/my_document.odt",
    doc_type="writer", 
    content="Hello, World!\n\nThis is my first LibreOffice document created via MCP."
)

# Create a Calc spreadsheet
result = create_document(
    path="/path/to/spreadsheet.ods",
    doc_type="calc"
)

# Create a Presentation 
result = create_document(
    path="/path/to/presentation.odp",
    doc_type="impress"
)

Reading Documents

# Read text content from any LibreOffice document
content = read_document_text("/path/to/document.odt")
print(f"Document has {content.word_count} words and {content.char_count} characters")
print(f"Content: {content.content}")

# Get document metadata
info = get_document_info("/path/to/document.odt")
print(f"File: {info.filename}, Size: {info.size_bytes} bytes")
print(f"Format: {info.format}, Modified: {info.modified_time}")

Document Conversion

# Convert ODT to PDF
result = convert_document(
    source_path="/path/to/document.odt",
    target_path="/path/to/document.pdf", 
    target_format="pdf"
)

if result.success:
    print("Conversion successful!")
else:
    print(f"Conversion failed: {result.error_message}")

# Convert to Microsoft Word format
result = convert_document(
    source_path="/path/to/document.odt",
    target_path="/path/to/document.docx",
    target_format="docx"
)

# Convert to HTML
result = convert_document(
    source_path="/path/to/document.odt", 
    target_path="/path/to/document.html",
    target_format="html"
)

Advanced Operations

Text Manipulation

# Add text to the end of a document
result = insert_text_at_position(
    path="/path/to/document.odt",
    text="\n\nThis text was added to the end of the document.",
    position="end"
)

# Insert text at the beginning
result = insert_text_at_position(
    path="/path/to/document.odt", 
    text="This is a new introduction.\n\n",
    position="start"
)

# Replace entire document content
result = insert_text_at_position(
    path="/path/to/document.odt",
    text="This completely replaces the document content.",
    position="replace"
)

Working with Spreadsheets

# Read data from a spreadsheet
data = read_spreadsheet_data(
    path="/path/to/spreadsheet.ods",
    sheet_name="Sheet1",  # Optional
    max_rows=50          # Optional, default 100
)

print(f"Sheet: {data.sheet_name}")
print(f"Dimensions: {data.row_count} rows × {data.col_count} columns")

# Access cell data
for row_idx, row in enumerate(data.data):
    for col_idx, cell in enumerate(row):
        print(f"Cell [{row_idx}][{col_idx}]: {cell}")

Document Search

# Search for documents containing specific text
results = search_documents(
    query="important project",
    search_path="/home/user/Documents"  # Optional
)

for doc in results:
    print(f"Found in: {doc['filename']}")
    print(f"Path: {doc['path']}")
    print(f"Context: {doc['match_context']}")

Batch Operations

# Convert all documents in a directory
results = batch_convert_documents(
    source_dir="/path/to/source_documents",
    target_dir="/path/to/converted_documents", 
    target_format="pdf",
    source_extensions=[".odt", ".doc", ".docx"]  # Optional
)

for result in results:
    if result.success:
        print(f"✓ Converted {result.source_path}")
    else:
        print(f"✗ Failed to convert {result.source_path}: {result.error_message}")

# Merge multiple documents
merged_doc = merge_text_documents(
    document_paths=[
        "/path/to/doc1.odt",
        "/path/to/doc2.odt", 
        "/path/to/doc3.odt"
    ],
    output_path="/path/to/merged_document.odt",
    separator="\n\n=== DOCUMENT BREAK ===\n\n"
)

Document Analysis

# Get detailed statistics about a document
stats = get_document_statistics("/path/to/document.odt")

file_info = stats['file_info']
content_stats = stats['content_stats']

print(f"File: {file_info['filename']}")
print(f"Size: {file_info['size_bytes']} bytes")
print(f"Words: {content_stats['word_count']}")
print(f"Characters: {content_stats['character_count']}")
print(f"Sentences: {content_stats['sentence_count']}")
print(f"Paragraphs: {content_stats['paragraph_count']}")
print(f"Average words per sentence: {content_stats['average_words_per_sentence']:.1f}")

Using Resources

The MCP server also provides resources for document discovery:

List All Documents

# Access via resource URI: documents://
# This will list all LibreOffice documents in common locations:
# - ~/Documents
# - ~/Desktop  
# - Current working directory

Access Document Content

# Access specific document content via resource URI: document://{path}
# Example: document://tmp/my_document.odt
# Returns formatted text content with metadata

Integration Examples

Claude Desktop Configuration

Add this to your Claude Desktop configuration file:

{
  "mcpServers": {
    "libreoffice": {
      "command": "uv",
      "args": ["run", "python", "/path/to/mcp-libre/main.py"],
      "cwd": "/path/to/mcp-libre",
      "env": {
        "PYTHONPATH": "/path/to/mcp-libre"
      }
    }
  }
}

Common Use Cases

  1. Document Processing Pipeline

    • Create documents from templates
    • Insert generated content
    • Convert to multiple formats for distribution

  2. Content Analysis

    • Extract text from various document formats
    • Analyze document statistics
    • Search across document collections

  3. Batch Document Management

    • Convert legacy documents to modern formats
    • Merge related documents
    • Generate reports from multiple sources

  4. Integration with AI Workflows

    • Process documents for AI analysis
    • Generate summaries and insights
    • Create formatted reports from AI-generated content

Error Handling

The server provides detailed error messages for common issues:

  • File not found: Clear error message with file path
  • Conversion failures: LibreOffice error output included
  • Permission issues: System-level error details
  • Format not supported: List of supported formats

Always check the success field in conversion results and handle errors appropriately in your applications.

Performance Considerations

  • Large documents: Text extraction may take time for very large files
  • Batch operations: Process documents in smaller batches for better performance
  • Spreadsheet data: Use max_rows parameter to limit data size
  • Concurrent operations: The server handles one operation at a time

Troubleshooting

  1. LibreOffice not found: Ensure LibreOffice is installed and in your PATH
  2. Java warnings: These are usually non-fatal; core functionality will still work
  3. Permission errors: Check file and directory permissions
  4. Conversion failures: Verify target format is supported by LibreOffice