---
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**