MCP/mcp-office-tools
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Update README with accurate tool documentation
Some checks are pending
Test Dashboard / test-and-dashboard (push) Waiting to run
Details

Browse Source 
- Document all 12 actual MCP tools (6 universal, 3 Word, 3 Excel)
- Add comprehensive format support matrix with feature breakdown
- Include practical usage examples with real output structures
- Add test dashboard section
- Simplify installation with uvx/Claude Code instructions
- Remove marketing fluff; focus on technical accuracy
This commit is contained in:
Ryan Malloy 2026-01-11 00:45:00 -07:00
parent c935cec7b6
commit 036160d029
1 changed files with 317 additions and 431 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

748
README.md
View File

@ -2,494 +2,380 @@
# 📊 MCP Office Tools # 📊 MCP Office Tools
<img src="https://img.shields.io/badge/MCP-Office%20Tools-blue?style=for-the-badge&logo=microsoft-office" alt="MCP Office Tools"> **Comprehensive Microsoft Office document processing for AI agents**
**🚀 The Ultimate Microsoft Office Document Processing Powerhouse for AI**
*Transform any Office document into actionable intelligence with blazing-fast, AI-ready processing*
[![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg?style=flat-square)](https://www.python.org/downloads/) [![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg?style=flat-square)](https://www.python.org/downloads/)
[![FastMCP](https://img.shields.io/badge/FastMCP-2.0+-green.svg?style=flat-square)](https://github.com/jlowin/fastmcp) [![FastMCP](https://img.shields.io/badge/FastMCP-0.5+-green.svg?style=flat-square)](https://gofastmcp.com)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=flat-square)](https://opensource.org/licenses/MIT) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=flat-square)](https://opensource.org/licenses/MIT)
[![Production Ready](https://img.shields.io/badge/status-production%20ready-brightgreen?style=flat-square)](https://github.com/MCP/mcp-office-tools) [![MCP Protocol](https://img.shields.io/badge/MCP-Protocol-purple?style=flat-square)](https://modelcontextprotocol.io)
[![MCP Protocol](https://img.shields.io/badge/MCP-1.13.0-purple?style=flat-square)](https://modelcontextprotocol.io)
*Extract text, tables, images, formulas, and metadata from Word, Excel, PowerPoint, and CSV files*
[Installation](#-installation) • [Tools](#-available-tools) • [Examples](#-usage-examples) • [Testing](#-testing)
</div> </div>
--- ---
## ✨ **What Makes MCP Office Tools Special?** ## ✨ Features
> 🎯 **The Problem**: Office documents are data goldmines, but extracting intelligence from them is painful, unreliable, and slow. - **Universal extraction** - Text, images, and metadata from any Office format
> - **Format-specific tools** - Deep analysis for Word, Excel, and PowerPoint
> ⚡ **The Solution**: MCP Office Tools delivers **lightning-fast, AI-optimized document processing** with **zero configuration** and **bulletproof reliability**. - **Intelligent pagination** - Large documents automatically chunked for AI context limits
- **Multi-library fallbacks** - Never fails silently; tries multiple extraction methods
<table> - **URL support** - Process documents directly from HTTP/HTTPS URLs with caching
<tr> - **Legacy format support** - Handles .doc, .xls, .ppt from Office 97-2003
<td>
### 🏆 **Why Choose Us?**
- **🚀 6x Faster** than traditional tools
- **🎯 99.9% Accuracy** with multi-library fallbacks
- **🔄 15+ Formats** including legacy Office files
- **🧠 AI-Ready** structured data extraction
- **⚡ Zero Setup** - works out of the box
- **🌐 URL Support** with smart caching
</td>
<td>
### 📈 **Perfect For:**
- **Business Intelligence** dashboards
- **Document Migration** projects
- **Content Analysis** pipelines
- **AI Training** data preparation
- **Compliance** and auditing
- **Research** and academia
</td>
</tr>
</table>
--- ---
## 🚀 **Get Started in 30 Seconds** ## 🚀 Installation
```bash ```bash
# 1️⃣ Install (choose your favorite) # Quick install with uvx (recommended)
uvx mcp-office-tools
# Or install with uv/pip
uv add mcp-office-tools uv add mcp-office-tools
# or: pip install mcp-office-tools pip install mcp-office-tools
# 2️⃣ Run the server
mcp-office-tools
# 3️⃣ Process documents instantly!
# (Works with Claude Desktop, API calls, or any MCP client)
``` ```
<details> ### Claude Desktop Configuration
<summary>🔧 <b>Claude Desktop Setup</b> (click to expand)</summary>
Add to your `claude_desktop_config.json`:
Add this to your `claude_desktop_config.json`:
```json ```json
{ {
"mcpServers": { "mcpServers": {
"mcp-office-tools": { "office-tools": {
"command": "mcp-office-tools" "command": "uvx",
"args": ["mcp-office-tools"]
} }
} }
} }
``` ```
*Restart Claude Desktop and you're ready to process Office documents!*
</details> ### Claude Code Configuration
---
## 🎭 **See It In Action**
### **📝 Word Documents → Structured Intelligence**
```python
# Extract everything from a Word document
result = await extract_text("quarterly-report.docx", preserve_formatting=True)
# Get instant insights
{
"text": "Q4 revenue increased by 23%...",
"word_count": 2847,
"character_count": 15920,
"extraction_time": 0.3,
"method_used": "python-docx",
"formatted_sections": [
{"type": "heading", "text": "Executive Summary", "level": 1},
{"type": "paragraph", "text": "Our Q4 performance exceeded expectations..."}
]
}
```
### **📊 Excel Spreadsheets → Pure Data Gold**
```python
# Process complex Excel files with ease
data = await extract_text("financial-model.xlsx", preserve_formatting=True)
# Returns clean, structured data ready for AI analysis
{
"text": "Revenue\t$2.4M\t$2.8M\t$3.1M\nExpenses\t$1.8M\t$1.9M\t$2.0M",
"method_used": "openpyxl",
"formatted_sections": [
{
"type": "worksheet",
"name": "Q4 Summary",
"data": [["Revenue", 2400000, 2800000, 3100000]]
}
]
}
```
### **🎯 PowerPoint → Key Insights Extracted**
```python
# Turn presentations into actionable content
slides = await extract_text("strategy-deck.pptx", preserve_formatting=True)
# Get slide-by-slide breakdown
{
"text": "Slide 1: Market Opportunity\nSlide 2: Competitive Analysis...",
"formatted_sections": [
{"type": "slide", "number": 1, "text": "Market Opportunity\n$50B TAM..."},
{"type": "slide", "number": 2, "text": "Competitive Analysis\nWe lead in..."}
]
}
```
---
## 🛠️ **Comprehensive Toolkit**
<div align="center">
| 🔧 **Tool** | 📋 **Purpose** | ⚡ **Speed** | 🎯 **Accuracy** |
|-------------|---------------|-------------|----------------|
| `extract_text` | Pull all text content with formatting | **Ultra Fast** | 99.9% |
| `extract_images` | Extract embedded images & media | **Fast** | 99% |
| `extract_metadata` | Document properties & statistics | **Instant** | 100% |
| `detect_office_format` | Smart format detection & validation | **Instant** | 100% |
| `analyze_document_health` | File integrity & corruption analysis | **Fast** | 98% |
| `get_supported_formats` | List all supported file types | **Instant** | 100% |
</div>
---
## 🌟 **Format Support Matrix**
<div align="center">
### **🎯 Universal Support Across All Office Formats**
| 📄 **Format** | 📝 **Text** | 🖼️ **Images** | 🏷️ **Metadata** | 🕰️ **Legacy** | 💪 **Status** |
|---------------|-------------|---------------|-----------------|---------------|----------------|
| `.docx` | ✅ Perfect | ✅ Perfect | ✅ Perfect | N/A | 🟢 **Production** |
| `.doc` | ✅ Excellent | ⚠️ Basic | ⚠️ Basic | ✅ Full | 🟢 **Production** |
| `.xlsx` | ✅ Perfect | ✅ Perfect | ✅ Perfect | N/A | 🟢 **Production** |
| `.xls` | ✅ Excellent | ⚠️ Basic | ⚠️ Basic | ✅ Full | 🟢 **Production** |
| `.pptx` | ✅ Perfect | ✅ Perfect | ✅ Perfect | N/A | 🟢 **Production** |
| `.ppt` | ✅ Good | ⚠️ Basic | ⚠️ Basic | ✅ Full | 🟡 **Stable** |
| `.csv` | ✅ Perfect | N/A | ⚠️ Basic | N/A | 🟢 **Production** |
*✅ Perfect • ⚠️ Basic • 🟢 Production Ready • 🟡 Stable*
</div>
---
## ⚡ **Blazing Fast Performance**
<div align="center">
### **📊 Real-World Benchmarks**
| 📄 **Document Type** | 📏 **Size** | ⏱️ **Processing Time** | 🚀 **Speed vs Competitors** |
|---------------------|------------|----------------------|---------------------------|
| Word Document | 50 pages | 0.3 seconds | **6x faster** |
| Excel Spreadsheet | 10 sheets | 0.8 seconds | **4x faster** |
| PowerPoint Deck | 25 slides | 0.5 seconds | **5x faster** |
| Legacy .doc | 100 pages | 1.2 seconds | **3x faster** |
*Benchmarked on: MacBook Pro M2, 16GB RAM*
</div>
---
## 🏗️ **Rock-Solid Architecture**
### **🔄 Multi-Library Fallback System**
*Never worry about document compatibility again*
```mermaid
graph TD
A[Document Input] --> B{Format Detection}
B -->|.docx| C[python-docx]
B -->|.doc| D[olefile]
B -->|.xlsx| E[openpyxl]
B -->|.xls| F[xlrd]
B -->|.pptx| G[python-pptx]
C -->|Success| H[✅ Extract Content]
C -->|Fail| I[mammoth fallback]
I -->|Fail| J[docx2txt fallback]
E -->|Success| H
E -->|Fail| K[pandas fallback]
G -->|Success| H
G -->|Fail| L[olefile fallback]
H --> M[🎯 Structured Output]
```
### **🧠 Intelligent Processing Pipeline**
1. **🔍 Smart Detection**: Automatically identify document type and best processing method
2. **⚡ Optimized Extraction**: Use the fastest, most accurate library for each format
3. **🛡️ Fallback Protection**: If primary method fails, seamlessly switch to backup
4. **🧹 Clean Output**: Deliver perfectly structured, AI-ready data every time
---
## 🌍 **Real-World Success Stories**
<div align="center">
### **🏢 Enterprise Use Cases**
</div>
<table>
<tr>
<td>
### **📊 Business Intelligence**
*Fortune 500 Financial Services*
**Challenge**: Process 10,000+ financial reports monthly
**Result**:
- ⚡ **95% time reduction** (20 hours → 1 hour)
- 🎯 **99.9% accuracy** in data extraction
- 💰 **$2M annual savings** in manual processing
</td>
<td>
### **🔄 Document Migration**
*Global Healthcare Provider*
**Challenge**: Migrate 50,000 legacy .doc files
**Result**:
- 📈 **100% success rate** with legacy formats
- ⏱️ **6 months → 2 weeks** completion time
- 🛡️ **Zero data loss** during migration
</td>
</tr>
<tr>
<td>
### **🔬 Research Analytics**
*Top University Medical School*
**Challenge**: Analyze 5,000 research papers
**Result**:
- 🚀 **10x faster** literature analysis
- 📋 **Structured data** ready for ML models
- 🎓 **3 published papers** from insights
</td>
<td>
### **🤖 AI Training Data**
*Silicon Valley AI Startup*
**Challenge**: Extract training data from documents
**Result**:
- 📊 **1M+ documents** processed flawlessly
- ⚡ **Real-time processing** pipeline
- 🧠 **40% better model accuracy**
</td>
</tr>
</table>
---
## 🎯 **Advanced Features That Set Us Apart**
### **🌐 URL Processing with Smart Caching**
```python
# Process documents directly from the web
doc_url = "https://company.com/annual-report.docx"
content = await extract_text(doc_url) # Downloads & caches automatically
# Second call uses cache - blazing fast!
cached_content = await extract_text(doc_url) # < 0.01 seconds
```
### **🩺 Document Health Analysis**
```python
# Get comprehensive document health insights
health = await analyze_document_health("suspicious-file.docx")
{
"overall_health": "healthy",
"health_score": 9,
"recommendations": ["Document appears healthy and ready for processing"],
"corruption_detected": false,
"password_protected": false
}
```
### **🔍 Intelligent Format Detection**
```python
# Automatically detect and validate any Office file
format_info = await detect_office_format("mystery-document")
{
"format_name": "Word Document (DOCX)",
"category": "word",
"is_legacy": false,
"supports_macros": false,
"processing_recommendations": ["Use python-docx for optimal results"]
}
```
---
## 📈 **Installation & Setup**
<details>
<summary>🚀 <b>Quick Install</b> (Recommended)</summary>
```bash ```bash
# Using uv (fastest) claude mcp add office-tools "uvx mcp-office-tools"
uv add mcp-office-tools
# Using pip
pip install mcp-office-tools
# From source (latest features)
git clone https://git.supported.systems/MCP/mcp-office-tools.git
cd mcp-office-tools
uv sync
``` ```
</details> ---
<details> ## 🛠 Available Tools
<summary>🐳 <b>Docker Setup</b></summary>
```dockerfile ### Universal Tools
FROM python:3.11-slim *Work with all Office formats: Word, Excel, PowerPoint, CSV*
RUN pip install mcp-office-tools
CMD ["mcp-office-tools"] | Tool | Description |
|------|-------------|
| `extract_text` | Extract text with optional formatting preservation |
| `extract_images` | Extract embedded images with size filtering |
| `extract_metadata` | Get document properties (author, dates, statistics) |
| `detect_office_format` | Identify format, version, encryption status |
| `analyze_document_health` | Check integrity, corruption, password protection |
| `get_supported_formats` | List all supported file extensions |
### Word Tools
| Tool | Description |
|------|-------------|
| `convert_to_markdown` | Convert to Markdown with automatic pagination for large docs |
| `extract_word_tables` | Extract tables as structured JSON, CSV, or Markdown |
| `analyze_word_structure` | Analyze headings, sections, styles, and document hierarchy |
### Excel Tools
| Tool | Description |
|------|-------------|
| `analyze_excel_data` | Statistical analysis: data types, missing values, outliers |
| `extract_excel_formulas` | Extract formulas with values and dependency analysis |
| `create_excel_chart_data` | Generate Chart.js/Plotly-ready data from spreadsheets |
---
## 📋 Format Support
| Format | Extension | Text | Images | Metadata | Tables | Formulas |
|--------|-----------|:----:|:------:|:--------:|:------:|:--------:|
| **Word (Modern)** | `.docx` | ✅ | ✅ | ✅ | ✅ | - |
| **Word (Legacy)** | `.doc` | ✅ | ⚠️ | ⚠️ | ⚠️ | - |
| **Word Template** | `.dotx` | ✅ | ✅ | ✅ | ✅ | - |
| **Word Macro** | `.docm` | ✅ | ✅ | ✅ | ✅ | - |
| **Excel (Modern)** | `.xlsx` | ✅ | ✅ | ✅ | ✅ | ✅ |
| **Excel (Legacy)** | `.xls` | ✅ | ⚠️ | ⚠️ | ✅ | ⚠️ |
| **Excel Template** | `.xltx` | ✅ | ✅ | ✅ | ✅ | ✅ |
| **Excel Macro** | `.xlsm` | ✅ | ✅ | ✅ | ✅ | ✅ |
| **PowerPoint (Modern)** | `.pptx` | ✅ | ✅ | ✅ | ✅ | - |
| **PowerPoint (Legacy)** | `.ppt` | ✅ | ⚠️ | ⚠️ | ⚠️ | - |
| **PowerPoint Template** | `.potx` | ✅ | ✅ | ✅ | ✅ | - |
| **CSV** | `.csv` | ✅ | - | ⚠️ | ✅ | - |
✅ Full support • ⚠️ Basic/partial support • - Not applicable
---
## 💡 Usage Examples
### Extract Text from Any Document
```python
# Simple extraction
result = await extract_text("report.docx")
print(result["text"])
# With formatting preserved
result = await extract_text(
file_path="report.docx",
preserve_formatting=True,
include_metadata=True
)
``` ```
</details> ### Convert Word to Markdown (with Pagination)
<details> ```python
<summary>🔧 <b>Development Setup</b></summary> # For large documents, results are automatically paginated
result = await convert_to_markdown("big-manual.docx")
# Continue with cursor for next page
if result.get("pagination", {}).get("has_more"):
next_page = await convert_to_markdown(
"big-manual.docx",
cursor_id=result["pagination"]["cursor_id"]
)
# Or use page ranges to get specific sections
result = await convert_to_markdown(
"big-manual.docx",
page_range="1-10"
)
# Or extract by chapter name
result = await convert_to_markdown(
"big-manual.docx",
chapter_name="Introduction"
)
```
### Analyze Excel Data Quality
```python
result = await analyze_excel_data(
file_path="sales-data.xlsx",
include_statistics=True,
check_data_quality=True
)
# Returns per-column analysis
# {
# "analysis": {
# "Sheet1": {
# "dimensions": {"rows": 1000, "columns": 12},
# "column_info": {
# "Revenue": {
# "data_type": "float64",
# "null_percentage": 2.3,
# "statistics": {"mean": 45000, "median": 42000, ...},
# "quality_issues": ["5 potential outliers"]
# }
# },
# "data_quality": {
# "completeness_percentage": 97.8,
# "duplicate_rows": 12
# }
# }
# }
# }
```
### Extract Excel Formulas
```python
result = await extract_excel_formulas(
file_path="financial-model.xlsx",
analyze_dependencies=True
)
# Returns formula details with dependency mapping
# {
# "formulas": {
# "Sheet1": [
# {
# "cell": "D2",
# "formula": "=B2*C2",
# "value": 1500.00,
# "dependencies": ["B2", "C2"]
# }
# ]
# }
# }
```
### Generate Chart Data
```python
result = await create_excel_chart_data(
file_path="quarterly-revenue.xlsx",
chart_type="line",
output_format="chartjs"
)
# Returns ready-to-use Chart.js configuration
# {
# "chartjs": {
# "type": "line",
# "data": {
# "labels": ["Q1", "Q2", "Q3", "Q4"],
# "datasets": [{"label": "Revenue", "data": [100, 120, 115, 140]}]
# }
# }
# }
```
### Extract Word Tables
```python
result = await extract_word_tables(
file_path="contract.docx",
output_format="markdown"
)
# Returns tables with optional format conversion
# {
# "tables": [
# {
# "table_index": 0,
# "dimensions": {"rows": 5, "columns": 3},
# "converted_output": "| Name | Role | Department |\n|---|---|---|\n..."
# }
# ]
# }
```
### Process Documents from URLs
```python
# Documents are downloaded and cached automatically
result = await extract_text("https://example.com/report.docx")
# Cache expires after 1 hour by default
```
---
## 🧪 Testing
The project includes a comprehensive test suite with an interactive HTML dashboard:
```bash ```bash
# Clone repository # Run all tests with dashboard generation
git clone https://git.supported.systems/MCP/mcp-office-tools.git make test
cd mcp-office-tools
# Install with development dependencies # Run just pytest
make test-pytest
# View the test dashboard
make view-dashboard
```
The test dashboard shows:
- Pass/fail statistics with MS Office-themed styling
- Detailed inputs and outputs for each test
- Expandable error tracebacks for failures
- Category breakdown (Word, Excel, PowerPoint)
---
## 🏗 Architecture
```
mcp-office-tools/
├── src/mcp_office_tools/
│ ├── server.py # FastMCP server entry point
│ ├── mixins/
│ │ ├── universal.py # Format-agnostic tools
│ │ ├── word.py # Word-specific tools
│ │ ├── excel.py # Excel-specific tools
│ │ └── powerpoint.py # PowerPoint tools (WIP)
│ ├── utils/
│ │ ├── validation.py # File validation
│ │ ├── file_detection.py # Format detection
│ │ ├── caching.py # URL caching
│ │ └── decorators.py # Error handling, defaults
│ └── pagination.py # Large document pagination
├── tests/ # pytest test suite
└── reports/ # Test dashboard output
```
### Processing Libraries
| Format | Primary Library | Fallback |
|--------|----------------|----------|
| `.docx` | python-docx | mammoth |
| `.xlsx` | openpyxl | pandas |
| `.pptx` | python-pptx | - |
| `.doc`/`.xls`/`.ppt` | olefile | - |
| `.csv` | pandas | built-in csv |
---
## 🔧 Development
```bash
# Clone and install
git clone https://github.com/yourusername/mcp-office-tools.git
cd mcp-office-tools
uv sync --dev uv sync --dev
# Run tests # Run tests
uv run pytest uv run pytest
# Code quality # Format and lint
uv run black src/ tests/ uv run black src/ tests/
uv run ruff check src/ tests/ uv run ruff check src/ tests/
# Type check
uv run mypy src/ uv run mypy src/
``` ```
</details> ---
## 📦 Dependencies
**Core:**
- `fastmcp` - MCP server framework
- `python-docx` - Word document processing
- `openpyxl` - Excel spreadsheet processing
- `python-pptx` - PowerPoint processing
- `pandas` - Data analysis and CSV handling
- `mammoth` - Word to HTML/Markdown conversion
- `olefile` - Legacy OLE format support
- `xlrd` - Legacy Excel support
- `pillow` - Image processing
- `aiohttp` / `aiofiles` - Async HTTP and file I/O
**Optional:**
- `python-magic` - Enhanced MIME type detection
- `msoffcrypto-tool` - Encrypted file detection
--- ---
## 🤝 **Integration Ecosystem** ## 🤝 Related Projects
### **🔗 Perfect Companion to MCP PDF Tools** - **[MCP PDF Tools](https://github.com/yourusername/mcp-pdf-tools)** - Companion server for PDF processing
- **[FastMCP](https://gofastmcp.com)** - The framework powering this server
```python
# Unified document processing across ALL formats
pdf_data = await pdf_tools.extract_text("report.pdf")
word_data = await office_tools.extract_text("report.docx")
excel_data = await office_tools.extract_text("data.xlsx")
# Cross-format document analysis
comparison = await compare_documents(pdf_data, word_data, excel_data)
```
### **⚡ Works With Your Favorite Tools**
- **🤖 Claude Desktop**: Native MCP integration
- **📊 Jupyter Notebooks**: Perfect for data analysis
- **🐍 Python Scripts**: Direct API access
- **🌐 Web Apps**: REST API wrappers
- **☁️ Cloud Functions**: Serverless deployment
--- ---
## 🛡️ **Enterprise-Grade Security** ## 📜 License
MIT License - see [LICENSE](LICENSE) for details.
---
<div align="center"> <div align="center">
| 🔒 **Security Feature** | ✅ **Status** | 📋 **Description** | **Built with [FastMCP](https://gofastmcp.com) and the [Model Context Protocol](https://modelcontextprotocol.io)**
|------------------------|---------------|-------------------|
| **Local Processing** | ✅ Enabled | Documents never leave your environment |
| **Automatic Cleanup** | ✅ Enabled | Temporary files removed after processing |
| **HTTPS-Only URLs** | ✅ Enforced | Secure downloads with certificate validation |
| **Memory Management** | ✅ Optimized | Efficient handling of large files |
| **No Data Collection** | ✅ Guaranteed | Zero telemetry or tracking |
</div> </div>
---
## 🚀 **What's Coming Next?**
<div align="center">
### **🔮 Roadmap 2024-2025**
</div>
| 🗓️ **Timeline** | 🎯 **Feature** | 📋 **Description** |
|-----------------|---------------|-------------------|
| **Q1 2025** | **Advanced Excel Tools** | Formula parsing, chart extraction, data validation |
| **Q2 2025** | **PowerPoint Pro** | Animation analysis, slide comparison, template detection |
| **Q3 2025** | **Document Conversion** | Cross-format conversion (Word→PDF, Excel→CSV, etc.) |
| **Q4 2025** | **Batch Processing** | Multi-document workflows with progress tracking |
| **2026** | **Cloud Integration** | Direct OneDrive, Google Drive, SharePoint support |
---
## 💝 **Community & Support**
<div align="center">
### **Join Our Growing Community!**
[![GitHub](https://img.shields.io/badge/GitHub-Repository-black?style=for-the-badge&logo=github)](https://git.supported.systems/MCP/mcp-office-tools)
[![Issues](https://img.shields.io/badge/Issues-Welcome-green?style=for-the-badge&logo=github)](https://git.supported.systems/MCP/mcp-office-tools/issues)
[![Discussions](https://img.shields.io/badge/Discussions-Join%20Us-blue?style=for-the-badge&logo=github)](https://git.supported.systems/MCP/mcp-office-tools/discussions)
**💬 Need Help?** Open an issue • **🐛 Found a Bug?** Report it • **💡 Have an Idea?** Share it!
</div>
---
<div align="center">
## 📜 **License & Credits**
**MIT License** - Use it anywhere, anytime, for anything!
**Built with ❤️ by the MCP Community**
*Powered by [FastMCP](https://github.com/jlowin/fastmcp) • [Model Context Protocol](https://modelcontextprotocol.io) • Modern Python*
---
### **⭐ If MCP Office Tools helps you, please star the repo! ⭐**
*It helps us build better tools for the community* 🚀
</div>