docx_mcp_server_ts
Enables programmatic processing of DOCX/OOXML files through MCP, covering text, tables, images, headers/footers, structured data tags, comments, and track changes.
README
DOCX MCP Server
A comprehensive TypeScript-based MCP (Model Context Protocol) server for universal DOCX processing with full OOXML support. Process Word documents programmatically with support for text, tables, images, headers/footers, SDTs, comments, and more.
Features
- Complete OOXML Access: Read/write DOCX parts at ZIP level with full namespace support
- Text Operations: Extract, find, and replace text with minimal diff preservation
- Table Management: Insert/delete rows, modify cells, merge/split operations
- Image Handling: Add inline/positioned images with EMU-based sizing
- Structured Data Tags (SDT): Access content controls by tag or alias
- Headers/Footers: List and modify section headers and footers
- Track Changes: Accept/reject revisions, handle insertions/deletions
- Comments: Manage document comments
- Metadata: Read/write core and app properties
- LRU Caching: Efficient memory management with part caching
- Lossless XML: Preserves document structure with fast-xml-parser
Installation
npm install
npm run build
Quick Start
Start the Server
npm start
The server will listen on stdin/stdout for MCP protocol messages.
Installation & Configuration
Claude Code CLI
claude mcp install docx \
--command node \
--args /full/path/to/docx_mcp_server_ts/dist/index.js \
--env LOG_LEVEL=INFO
~/.claude.json (для Claude Code)
Отредактировать ~/.claude.json добавить в раздел "projects":
{
"projects": {
"/full/path/to/docx_mcp_server_ts": {
"mcpServers": {
"docx": {
"command": "node",
"args": ["/full/path/to/docx_mcp_server_ts/dist/index.js"],
"env": {
"LOG_LEVEL": "INFO"
}
}
}
}
}
}
Пример для Linux/WSL:
{
"projects": {
"/mnt/c/Users/pavelk/Desktop/Projects/MCP-servers/docx_mcp_server_ts": {
"mcpServers": {
"docx": {
"command": "node",
"args": ["/mnt/c/Users/pavelk/Desktop/Projects/MCP-servers/docx_mcp_server_ts/dist/index.js"],
"env": {
"LOG_LEVEL": "INFO"
}
}
}
}
}
}
MCP Tools
Document Management
docx.open
Open a DOCX document from file or base64 buffer.
Input:
{
"path": "/path/to/document.docx",
"bufferBase64": "..." // OR provide base64 data
}
Output:
{
"docId": "uuid-string",
"parts": ["word/document.xml", ...],
"props": { "core": {}, "app": {} }
}
docx.close
Close a document and release resources.
Input: { "docId": "uuid" }
docx.save
Save document to file or return as base64.
Input:
{
"docId": "uuid",
"path": "/output/path.docx", // optional
"returnBase64": true // optional
}
docx.list_parts
List all parts in document.
docx.part_read / docx.part_write
Read/write individual XML parts for low-level access.
Text Operations
docx.get_text
Extract all text from document.
Input: { "docId": "uuid", "scope": "document|headers|footers|all" }
docx.replace_text
Replace text preserving run structure.
Input:
{
"docId": "uuid",
"match": "search text",
"replace": "replacement",
"mode": "literal|regex",
"where": "document|headers|footers|all"
}
Output: { "replaced": 5 }
docx.find
Find text with context.
Output:
{
"hits": [
{
"text": "found text",
"context": "...found text...",
"offset": 150
}
]
}
Table Operations
docx.tables_list
List all tables with dimensions.
Output:
{
"tables": [
{
"tableXPath": "//w:tbl[1]",
"rows": 5,
"colsApprox": 3
}
]
}
docx.table_edit
Perform table operations.
Input:
{
"docId": "uuid",
"tableXPath": "//w:tbl[1]",
"op": {
"kind": "setCellText",
"row": 0,
"col": 0,
"text": "new value"
}
}
Supported operations:
{ "kind": "setCellText", "row": number, "col": number, "text": string }{ "kind": "insertRow", "at": number }{ "kind": "deleteRow", "at": number }{ "kind": "insertCol", "at": number }{ "kind": "deleteCol", "at": number }
Structured Data Tags (SDT)
docx.sdt_get
Get content control content.
Input: { "docId": "uuid", "tagOrAlias": "control_tag" }
Output:
{
"xml": "<w:p>...</w:p>",
"textPreview": "Control content..."
}
docx.sdt_put
Update content control.
Input:
{
"docId": "uuid",
"tagOrAlias": "control_tag",
"xmlFragment": "<w:p>...</w:p>"
}
Image Operations
docx.images_list
List all images with metadata.
Output:
{
"images": [
{
"rId": "rId4",
"path": "word/media/image1.png",
"sizeEMU": { "cx": 914400, "cy": 914400 }
}
]
}
docx.image_add
Insert image inline or anchored.
Input:
{
"docId": "uuid",
"target": {
"afterParagraphXPath": "//w:p[1]",
"sdtTagOrAlias": "imageControl" // OR use SDT
},
"image": {
"path": "/local/image.png",
"base64": "...", // OR base64 data
"filename": "image.png",
"contentType": "image/png"
},
"placement": {
"kind": "inline" // OR { "kind": "anchor", "xEMU": 0, "yEMU": 0 }
},
"size": {
"widthMM": 50,
"heightMM": 50
},
"altText": "Description"
}
docx.image_update_position
Update anchored image position/size.
Advanced Operations
docx.styles_get / docx.styles_set
Read/write styles.xml
docx.numbering_get / docx.numbering_set
Read/write numbering.xml
docx.headers_footers_list
List headers and footers with section info.
docx.headers_footers_get / docx.headers_footers_set
Read/write specific header or footer.
docx.comments_list / docx.comments_add / docx.comments_delete
Manage document comments.
docx.changes_accept_all
Accept all tracked changes (remove w:del, unwrap w:ins).
Output: { "removedDel": 3, "flattenedIns": 5 }
docx.metadata_get / docx.metadata_set
Read/write document properties (core.xml, app.xml).
Size Conversions
The server handles EMU (English Metric Unit) conversions internally:
- 1 inch = 914,400 EMU
- 1 mm ≈ 36,000 EMU
- 1 point ≈ 12,700 EMU
Examples
Extract and Replace Text
// Open document
const openResult = await client.call('docx.open', {
path: '/tmp/document.docx'
});
const docId = openResult.docId;
// Get text
const textResult = await client.call('docx.get_text', { docId });
console.log(textResult.text);
// Replace text
await client.call('docx.replace_text', {
docId,
match: 'old text',
replace: 'new text',
mode: 'literal'
});
// Save
await client.call('docx.save', {
docId,
path: '/tmp/document-modified.docx'
});
// Close
await client.call('docx.close', { docId });
Modify Table
// List tables
const tablesResult = await client.call('docx.tables_list', { docId });
const tableXPath = tablesResult.tables[0].tableXPath;
// Update cell
await client.call('docx.table_edit', {
docId,
tableXPath,
op: {
kind: 'setCellText',
row: 0,
col: 0,
text: 'Updated Value'
}
});
// Insert row
await client.call('docx.table_edit', {
docId,
tableXPath,
op: {
kind: 'insertRow',
at: 1
}
});
Add Image
const fs = require('fs').promises;
const imageBuffer = await fs.readFile('/path/to/image.png');
const base64 = imageBuffer.toString('base64');
await client.call('docx.image_add', {
docId,
target: {
afterParagraphXPath: '//w:p[1]'
},
image: {
base64,
filename: 'image.png',
contentType: 'image/png'
},
placement: {
kind: 'inline'
},
size: {
widthMM: 100,
heightMM: 75
},
altText: 'My image'
});
Architecture
src/
├── index.ts # MCP server entry point
├── logger.ts # Logging utility
├── errors.ts # Error types and codes
├── ooxml/
│ ├── namespaces.ts # OOXML constants and namespaces
│ ├── emu.ts # Unit conversion utilities
│ ├── dom.ts # XML DOM utilities (xmldom + fontoxpath)
│ ├── xmlParser.ts # FXP parser with order preservation
│ ├── parts.ts # ZIP part reading/writing
│ ├── rels.ts # Relationship management
│ ├── text.ts # Text operations with diff-match-patch
│ ├── tables.ts # Table manipulation
│ ├── sdt.ts # Structured Data Tags
│ ├── drawings.ts # Image handling
│ ├── headersFooters.ts # Header/footer operations
│ ├── comments.ts # Comment management
│ ├── changes.ts # Track changes handling
│ ├── styles.ts # Styles XML access
│ └── numbering.ts # Numbering XML access
├── store/
│ ├── types.ts # Store type definitions
│ └── docStore.ts # Document store with LRU cache
└── mcp/
└── tools.ts # MCP tool implementations
Performance
- Memory: LRU cache limits per-document parts to 50 cached items
- Total Size: Supports documents up to 100MB in-memory
- Partial Access: Only requested parts are parsed from ZIP
- Minimal Diffs: Text replacements preserve run structure when possible
Limitations
- Page layout calculations are not performed (Word's rendering engine needed)
- Advanced DrawingML transformations are read-only
- VBA macros and embedded OLE objects not supported
- Extremely large documents (>500MB) may require streaming
Development
# Install dependencies
npm install
# Type check
npm run type-check
# Build
npm run build
# Run dev server
npm run dev
# Debug with inspector
npm run dev:debug
Logging
Control log level via environment variable:
LOG_LEVEL=DEBUG npm start # Verbose
LOG_LEVEL=INFO npm start # Default
LOG_LEVEL=WARN npm start # Warnings only
LOG_LEVEL=ERROR npm start # Errors only
Protocol Support
- Transport: stdio
- Protocol: MCP (Model Context Protocol)
- Handler: @modelcontextprotocol/sdk
License
MIT
Resources
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.