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---
title: MCP File Processor Tool
emoji: 📁
colorFrom: yellow
colorTo: red
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: false
license: mit
tags:
- mcp-server-track
- mcp
- file-processing
- document-analysis
- data-extraction
- hackathon
- gradio
python_version: 3.11.8
---
# 📁 MCP File Processor Tool
An AI-powered file processing tool that provides both a user-friendly Gradio interface and an MCP (Model Context Protocol) server endpoint for integration with AI assistants and other applications.
## ✨ Features
- **📄 Multi-Format Support**: Process CSV, JSON, TXT, and other document formats
- **🔍 Smart Analysis**: Extract content, structure, and metadata from uploaded files
- **📊 Data Insights**: Provide statistical analysis and content summaries
- **🔌 MCP Server**: Compliant with Model Context Protocol for AI assistant integration
- **🎨 Interactive UI**: Modern Gradio interface with drag-and-drop file upload
- **⚡ Fast Processing**: Efficient file parsing and analysis capabilities
## 🚀 Quick Start
### Using the Web Interface
1. **Visit this Space** and interact with the web interface directly
2. **Upload your file** using the drag-and-drop interface
3. **View analysis results** including content extraction and insights
4. **Download processed data** in various formats
### Supported File Types
- 📊 **CSV Files**: Data analysis, column profiling, statistical summaries
- 📋 **JSON Files**: Structure analysis, key exploration, validation
- 📄 **Text Files**: Content extraction, word counts, encoding detection
- 📑 **Documents**: Basic text extraction and metadata analysis
## 🔌 MCP Server Integration
This tool implements the Model Context Protocol (MCP) for integration with AI assistants, allowing programmatic file processing capabilities.
### MCP Endpoint Details
- **Endpoint URL**: `https://[this-space-url]/gradio_api/mcp/sse`
- **HTTP Method**: `POST`
- **Content-Type**: `application/json`
### Request Format
Send a POST request with the following JSON payload:
```json
{
"data": [
"<file_content_or_path>",
"<processing_type>"
]
}
```
**Parameters:**
- `data[0]` (string): File content or file path to process
- `data[1]` (string): Processing type ("analyze", "extract", "summarize")
### Response Format
Successful responses return:
```json
{
"data": [
{
"status": "success",
"file_type": "csv",
"analysis": {
"rows": 1000,
"columns": 5,
"summary": "Data analysis results..."
},
"content": "Processed content or insights..."
}
]
}
```
## 🎯 Use Cases for AI Assistants
When integrated with AI assistants via MCP, this tool enables:
1. **Data Analysis**: "Analyze this CSV file and provide insights"
2. **Content Extraction**: "Extract text content from this document"
3. **File Validation**: "Check if this JSON file is properly formatted"
4. **Data Summary**: "Summarize the key information in this file"
5. **Batch Processing**: "Process multiple files and compare results"
## 🛠️ Technical Details
### Processing Capabilities
- **CSV Analysis**: Column types, statistics, missing values, correlations
- **JSON Validation**: Structure validation, key analysis, nested object exploration
- **Text Processing**: Encoding detection, word count, language detection
- **Metadata Extraction**: File size, creation date, format details
### API Configuration
- **Timeout**: 60 seconds for large file processing
- **Size Limits**: 50MB maximum file size
- **Rate Limiting**: Standard Gradio Space limits
- **Error Handling**: Comprehensive error messages and recovery
## 🏆 Hackathon Submission
This tool is submitted for the **MCP Server Track** of the hackathon, demonstrating:
- ✅ **MCP Protocol Compliance**: Full implementation of MCP server specification
- ✅ **Production Ready**: Robust error handling and file validation
- ✅ **User Experience**: Intuitive file upload interface with previews
- ✅ **Documentation**: Comprehensive API documentation and examples
- ✅ **Integration Ready**: Easy to integrate with AI assistants and workflows
## 🔧 Local Development
### Prerequisites
- Python 3.11+
- Required packages for file processing (pandas, json, csv)
### Installation
```bash
# Clone this repository
git clone [repository-url]
cd mcp_file_processor_gradio
# Install dependencies
pip install -r requirements.txt
# Run the application
python app.py
```
### Testing MCP Endpoint Locally
```bash
# Test with curl
curl -X POST http://localhost:7860/gradio_api/mcp/sse \
-H "Content-Type: application/json" \
-d '{"data": ["sample_data.csv", "analyze"]}'
```
## 📊 Performance & Limitations
### Strengths
- Fast file processing and analysis
- Multi-format support
- Comprehensive error handling
- MCP protocol compliance
### Limitations
- 50MB file size limit
- Processing time depends on file size
- Limited to common file formats
- Requires well-formatted input files
## 📝 License
MIT License - Feel free to use and modify for your projects.
## 🤝 Contributing
This is a hackathon submission, but feedback and suggestions are welcome!
## 🏷️ Tags
`#mcp-server-track` `#file-processing` `#data-analysis` `#gradio` `#ai-assistant` `#model-context-protocol`
---
**Built with ❤️ for the MCP Hackathon** |