Skip to main content

Docx_MCP

9/12/26About 7 min

Docx_MCP

A powerful Word document processing MCP service that provides a complete document processing solution, including document structure extraction, content modification, and cloud storage integration. It…

📚 DOCX MCP Complete User Guide

🌟 Project Overview

DOCX MCP is a powerful Word document processing tool based on the MCP (Model Context Protocol) protocol, providing 42 professional document processing tools that support advanced features such as intelligent table analysis, automated filling, and document generation.

Core Features

  • 🎯 42 MCP Tools: Covering comprehensive functions including document management, table processing, and image editing
  • 🤖 AI Friendly: Perfectly compatible with AI assistants like Claude and ChatGPT
  • 📊 Intelligent Tables: Automatically recognize table structures and intelligently fill data
  • 🎨 Rich Formatting: Support for fine-grained control over text, images, and tables
  • 🚀 High Performance: Based on the FastMCP framework for quick response
  • 🔧 Easy Integration: Standard MCP protocol for easy integration into various applications

📦 Quick Installation

bash pip install docx-mcp

Method 2: Using uv (Faster)

bash uv pip install docx-mcp

Method 3: Using uvx (Temporary Run)

bash uvx docx-mcp

Verify Installation

bash

Check version

pip show docx-mcp

Test command

docx-mcp --help

🚀 Quick Start

1. Running as an MCP Server

bash

Start the MCP server

docx-mcp

Or use uvx (no installation required)

uvx docx-mcp

After the server starts, it will display: plaintext Starting the final complete MCP server... Function modules:

  • 📊 Tool Categories (42)
  • 📁 Document Management Tools (8)
  • ✍️ Text Content Tools (5)
  • 📊 Table Operation Tools (6)
  • 🔍 Table Analysis Tools (5)
  • 📝 Table Filling Tools (4)
  • 🖼️ Image Processing Tools (3)
  • 📐 Page Setup Tools (3)
  • 🧠 Intelligent Function Tools (5)
  • ⚙️ System Status Tools (3) ... Total: 42 tools

2. Configuring Claude Desktop

Edit claude_desktop_config.json:

json { "mcpServers": { "docx-mcp": { "command": "uvx", "args": ["docx-mcp"] } } }

Configuration File Location:

  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json

🛠️ Full List of 42 Tools

📁 Document Management Tools (8)

1. create_document

Create a new Word document

Parameters:

  • file_path (required): Path to save the document

Example: python create_document("report.docx")

2. open_document

Open an existing document

Parameters:

  • file_path (required): Path to the document

3. save_document

Save the current document

4. save_as_document

Save as a new document

Parameters:

  • new_file_path (required): Path to the new document

5. close_document

Close the current document

6. get_document_info

Get document information (number of paragraphs, number of tables, etc.)

7. copy_document

Copy the document to a new location

Parameters:

  • source_path (required): Source file path
  • target_path (required): Target path

8. create_work_copy

Create a working copy of the document

Parameters:

  • file_path (required): Original file path
  • suffix (optional): Suffix, default is "_工作版"

✍️ Text Content Tools (5)

9. add_paragraph

Add a paragraph

Parameters:

  • text (required): Paragraph text
  • bold (optional): Whether to bold
  • italic (optional): Whether to italicize
  • underline (optional): Whether to underline
  • font_size (optional): Font size
  • font_name (optional): Font name
  • color (optional): Color (hexadecimal)
  • alignment (optional): Alignment

Example: python add_paragraph( text="This is important content", bold=True, font_size=14, color="#FF0000", alignment="center" )

10. add_heading

Add a heading

Parameters:

  • text (required): Heading text
  • level (optional): Heading level (1-9)

11. add_text_with_formatting

Add precisely formatted text

12. search_and_replace

Search and replace text

Parameters:- search_text (required): Search text

  • replace_text (required): Replacement text
  • case_sensitive (optional): Whether to be case sensitive

13. smart_add_content

Intelligently add content (automatically recognize type)

Parameters:

  • content (required): Content
  • content_type (optional): Type (paragraph/heading/list)
  • style (optional): Style (normal/emphasis/quote)
  • auto_format (optional): Auto format

📊 Table Operation Tools (6)

14. add_table

Add a table

Parameters:

  • rows (required): Number of rows
  • cols (required): Number of columns
  • data (optional): Table data (2D array)
  • has_header (optional): Whether it has a header

Example: python add_table( rows=3, cols=3, data=[ ["Name", "Age", "Occupation"], ["Zhang San", "25", "Engineer"], ["Li Si", "30", "Designer"] ], has_header=True )

15. add_table_row

Add a table row

Parameters:

  • table_index (required): Table index
  • row_data (required): Row data array

16. add_table_column

Add a table column

Parameters:

  • table_index (required): Table index
  • column_index (optional): Insertion position
  • data (optional): Column data

17. format_table

Format a table

Parameters:

  • table_index (required): Table index
  • style (optional): Table style

18. merge_table_cells

Merge table cells

Parameters:

  • table_index (required): Table index
  • row_start (required): Start row
  • col_start (required): Start column
  • row_end (required): End row
  • col_end (required): End column

19. intelligent_create_table

Intelligently create a table (automatic styling)

Parameters:

  • data (required): Table data (2D array)
  • auto_style (optional): Automatically apply style

🔍 Table Analysis Tools (5)

20. extract_table_structure

Extract table structure (full analysis)

Parameters:

  • file_path (required): Document path
  • table_index (required): Table index

Returns: Detailed table structure in JSON format

Example: python structure = extract_table_structure("report.docx", 0)

Returns: number of rows and columns, cell contents, merge information, etc.

21. extract_all_tables_structure

Extract all table structures

Parameters:

  • file_path (required): Document path

22. extract_document_structure

Extract full document structure

Parameters:

  • file_path (required): Document path
  • include_cell_details (optional): Whether to include cell details

23. get_table_structure_cache_info

Get table structure cache information

24. clear_table_structure_cache

Clear table structure cache

📝 Table Filling Tools (4)

25. extract_fillable_fields

Extract fillable fields (coordinate-specific)

Parameters:

  • file_path (required): Document path

Returns: Field coordinate mapping, empty space information, filling suggestions

Example: python fields = extract_fillable_fields("template.docx")

Returns: {"field_coordinates": {"Name": [0, 1, 2]}, ...}

26. fill_with_coordinates

Fill using coordinates (main function)

Parameters:

  • file_path (required): Document path
  • coordinate_data (required): Coordinate data dictionary

Example: python fill_with_coordinates( "template.docx", { "Zhang San": [0, 1, 2], # [table index, row, column] "2023001": [0, 2, 2], "School of Computer Science": [0, 3, 2] } )

27. basic_table_fill

Basic table filling (smart matching)

Parameters:

  • file_path (required): Document path
  • fill_data (required): Fill data dictionary

Example: python basic_table_fill( "template.docx", { "Name": "Zhang San", "Student ID": "2023001", "School": "School of Computer Science", "Major": "Computer Science and Technology" } )

28. intelligent_table_fill

Intelligent table filling (auxiliary function)

🖼️ Image Processing Tools (3)

29. add_image

Add an image

Parameters:- image_path (required): Image path

  • width (optional): Width (in inches)
  • height (optional): Height (in inches)

Example: python add_image("logo.png", width=3, height=2)

30. extract_images

Extracts all images from the document

Parameters:

  • output_dir (optional): Output directory

31. resize_image

Resizes an image

Parameters:

  • image_index (required): Image index
  • width (required): New width
  • height (required): New height

📐 Page Setup Tools (3)

32. set_page_margins

Sets page margins

Parameters:

  • top (optional): Top margin (in inches)
  • bottom (optional): Bottom margin
  • left (optional): Left margin
  • right (optional): Right margin

Example: python set_page_margins(top=1, bottom=1, left=1.5, right=1.5)

33. set_page_orientation

Sets page orientation

Parameters:

  • orientation (optional): portrait (portrait) or landscape (landscape)

34. set_page_size

Sets page size

Parameters:

  • width (optional): Width (in inches)
  • height (optional): Height (in inches)

🧠 Intelligent Function Tools (5)

35. intelligent_create_document

Intelligently creates a document (with template)

Parameters:

  • file_path (required): Document path
  • template_type (optional): Template type
    • basic: Basic document
    • business: Business document
    • academic: Academic paper
  • auto_optimize (optional): Automatically optimize pages

Example: python intelligent_create_document( "report.docx", template_type="business", auto_optimize=True )

36. get_smart_suggestions

Gets smart suggestions

Parameters:

  • context (optional): Context type
    • document_editing: Document editing
    • table_creation: Table creation
    • content_formatting: Content formatting
    • structure_optimization: Structure optimization
    • professional_polish: Professional polish

37. get_intelligent_planning_guide

Gets intelligent planning guide

Returns: A complete guide for using MCP tools with AI

38. create_intelligent_workflow_plan

Creates an intelligent workflow plan

Parameters:

  • user_request (required): User request description

Returns: A detailed tool call plan

39. get_tool_detailed_guidance

Gets detailed guidance for a tool

Parameters:

  • tool_name (required): Tool name

⚙️ System Status Tools (3)

40. get_system_status

Gets system status

Returns: Current document status, list of available tools, etc.

41. test_connection

Tests connection

Returns: Connection status confirmation

42. get_server_info

Gets server information

Returns: Server version, feature list, etc.

💡 Usage Scenario Examples

Scenario 1: Batch Report Generation

python from final_complete_server import *

1. Create document

intelligent_create_document("report.docx", "business", True)

2. Add heading

add_heading("Monthly Work Report", level=1)

3. Add table

intelligent_create_table([ ["Project Name", "Completion Rate", "Notes"], ["Project A", "100%", "Completed"], ["Project B", "80%", "In Progress"] ])

4. Save

save_document()

Scenario 2: Intelligent Form Filling

python from core.universal_table_filler import UniversalTableFiller

filler = UniversalTableFiller()

1. Analyze table structure

coordinates = filler.analyze_and_get_coordinates("template.docx")

2. Prepare data

data = { "Name": "Zhang San", "Student ID": "2023001", "College": "School of Computer Science", "Major": "Computer Science and Technology", "Contact": "13800138000" }

3. Intelligent fill

fill_with_coordinates("template.docx", { "Zhang San": [0, 1, 2], "2023001": [0, 2, 2], "School of Computer Science": [0, 3, 2], "Computer Science and Technology": [0, 4, 2], "13800138000": [0, 5, 2] })

Scenario 3: Batch Document Processing

python import os from pathlib import Path

Batch process all documents in a folder

folder = Path("documents") for doc in folder.glob("*.docx"): # Open document open_document(str(doc))

# Add page number
add_paragraph(f"Page ``", alignment="center")

# Set uniform margins
set_page_margins(1, 1, 1, 1)

# Save
save_document()
close_document()---

🎯 Advanced Features

1. Table Structure Analysis

python from core.table_structure_extractor import table_extractor

Extract table structure

structure = table_extractor.extract_table_structure("document.docx", 0)

Get table information

print(f"Number of rows: {structure.rows}") print(f"Number of columns: {structure.columns}") print(f"Table type: {structure.table_type}") print(f"Page format: {structure.page_format}")

Traverse cells

for row in structure.cells: for cell in row: print(f"({cell.row_index}, {cell.col_index}): {cell.text}")

2. Intelligent Workflow Planning

python from core.intelligent_tool_planner import intelligent_planner

Get tool planning

plan = intelligent_planner.create_intelligent_plan( "Create a student information table, including name, student ID, and class, and fill with example data" )

Execute according to the plan

for step in plan.workflow_steps: print(f"Step {step.step_id}: {step.description}") print(f"Tool: {step.tool_name}") print(f"Parameters: {step.parameters}")

3. Custom Templates

python

Create a custom business template

intelligent_create_document("template.docx", "business")

Add company information

add_paragraph("ABC Company", bold=True, font_size=16, alignment="center") add_paragraph("Address: No. XX, XX Road, XX City") add_paragraph("Phone: 021-12345678")

Add table framework

add_table(10, 3, has_header=True)

Save as template

save_as_document("custom_template.docx")

🔧 Configuration and Optimization

Environment Variable Configuration

bash

Set cache directory

export UV_CACHE_DIR=/path/to/cache

Disable progress bar

export UV_NO_PROGRESS=1

Use domestic mirror

export UV_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple

Performance Optimization Suggestions

  1. Use Cache: Table structures are automatically cached, improving the speed of repeated operations.
  2. Batch Operations: Try to complete multiple operations at once after opening the document.
  3. Reasonable Tool Usage: Choose the appropriate tool based on your needs (e.g., basic vs. intelligent).

🐛 Frequently Asked Questions

Q1: What to do if installation fails?

bash

Method 1: Use domestic mirror

pip install docx-mcp -i https://pypi.tuna.tsinghua.edu.cn/simple

Method 2: Upgrade pip

python -m pip install --upgrade pip pip install docx-mcp

Method 3: Use uv (faster)

curl -LsSf https://astral.sh/uv/install.sh | sh uv pip install docx-mcp

Q2: Module import failure?

python

Ensure correct import method

from final_complete_server import mcp # ✅ Correct

from docx_mcp import mcp # ❌ Incorrect

Q3: Inaccurate table filling?

python

Recommended to use coordinate-based filling

1. Analyze structure first

fields = extract_fillable_fields("template.docx")

2. Fill based on returned coordinate information

fill_with_coordinates("template.docx", coordinate_data)

Q4: How to debug?

python

Enable detailed logging

import logging logging.basicConfig(level=logging.DEBUG)

View tool list

status = get_system_status() print(status)

📝 API Reference

Python API

python

Import method

from final_complete_server import mcp from core.universal_table_filler import UniversalTableFiller from core.intelligent_table_analyzer import IntelligentTableAnalyzer from core.table_structure_extractor import table_extractor

MCP Protocol API

When running as an MCP server, call tools via the standard MCP protocol:

json { "jsonrpc": "2.0", "method": "tools/call", "params": { "name": "create_document", "arguments": { "file_path": "example.docx" } } }

  • PyPI: https://pypi.org/project/docx-mcp/
  • GitHub: https://github.com/rockcj/Docx_MCP_cj
  • Issue Feedback: https://github.com/rockcj/Docx_MCP_cj/issues
  • MCP Protocol: https://modelcontextprotocol.io/
  • FastMCP: https://gofastmcp.com

📄 License

MIT License

🙏 AcknowledgmentsThank you to all contributors and users for your support!

Version: 0.1.6
Update Date: 2025-10-02
Author: DOCX MCP Team

📞 Getting Help

If you encounter any issues or need assistance:

  1. Check the FAQ section of this document
  2. Visit the GitHub Issues page
  3. Review the example code
  4. Contact the maintenance team

Happy Documenting! 📝✨

**Official site: ** https://github.com/rockcj/Docx_MCP_cj.git **Status: ** active　**Last verified: ** 2026-08-30

Categories & Tags

  • Categories: files
  • Tags: file systems, ai智能化处理docx文档助手, chinese

MCP Configuration

  • Transport: stdio
  • Command: uvx
  • Args: docx-mcp

This config can be imported into ChatSpeed from the resource index. Verify the command, arguments, and permission source are trustworthy before importing.

Data source

Resource file: resources/mcp/rockcj-docx.json. Content last verified on 2026-08-30; free quotas and service limits may change with official policies.