iMAGRAY/FileForge
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FileForge v3.2 is a cutting-edge Model Context Protocol (MCP) server designed to transform raw code into optimized solutions with enhanced performance and vector embeddings support.
🔥 FileForge v3.2
🔥 FileForge - The ultimate file and code forge! Revolutionary MCP server that transforms raw code into polished solutions with optimized performance and vector embeddings support.
⚡ Quick Setup
Use directly from Git (no download needed):
{
"mcpServers": {
"fileforge": {
"command": "npx",
"args": ["--yes", "github:iMAGRAY/FileForge", "node", "src/fileforge.cjs"]
}
}
}
Copy this into your MCP client configuration and you're ready to go!
Want a specific version? Use: "github:iMAGRAY/FileForge#v3.2.0"
📋 See for configurations for Claude Desktop, Cursor, Continue.dev and more!
✨ Key Features
- 🔧 17 useful tools for code management
- ⚡ Optimized file operations with improved performance
- 🧠 Vector embeddings system for semantic code search
- 🛡️ Multi-level error protection with automatic recovery
- 💾 Chunked reading for working with files of any size
- 🔄 Automatic backup with rollback functionality
- 🎯 Intelligent path normalization for cross-platform compatibility
🎛️ Available Tools
📁 File Operations
create_file- Create new files with automatic directory creationread_file_chunked- Read files in chunks (50-1000 lines at a time)replace_lines- Replace line ranges with backupdelete_lines- Delete lines with rollback capabilityinsert_lines- Insert new lines into file
🔍 Code Analysis
find_code_structures- Find functions, classes, methods in codefind_and_replace- Advanced search and replace with regex supportgenerate_diff- Generate detailed diff between files
🚀 Batch Operations
batch_operations- Bulk operations (copy, move, delete, mkdir)process_multiple_files- Process multiple files (9 operations)process_file_complete- Complete file analysis with metrics
🧠 Vector Embeddings
smart_create_embedding- Smart embedding creation (skip existing)cleanup_file_embedding- Remove file embeddingsget_embedding_cache_info- Embedding cache statisticshas_embedding- Quick embedding existence check (<1ms)
🛠️ Management System
rollback_operation- Rollback operations by IDget_performance_stats- Detailed performance statistics
🚀 Quick Start
🔥 Path Handling Features
FileForge automatically works with relative paths from the project root:
- Root directory: folder containing
src/fileforge.cjs - Relative paths:
./README.md,docs/guide.md - Absolute paths:
C:/full/path/to/file.txt
🚀 Installation Options
Option 1: Direct from Git (Recommended)
No need to clone! Use FileForge directly from GitHub:
{
"mcpServers": {
"fileforge": {
"command": "npx",
"args": [
"--yes",
"github:iMAGRAY/FileForge",
"node",
"src/fileforge.cjs"
],
"env": {
"NODE_PATH": "./node_modules"
}
}
}
}
Option 2: Local Installation
1. Clone Repository
git clone https://github.com/iMAGRAY/FileForge.git
cd FileForge
2. Install Dependencies
# Install Node.js dependencies
npm install
# Install Python dependencies
pip install -r requirements.txt
3. Build C++ Components (Optional)
# Linux/macOS
make
# Windows
build_vs.bat
4. Configure MCP
{
"mcpServers": {
"fileforge": {
"command": "node",
"args": ["path/to/FileForge/src/fileforge.cjs"]
}
}
}
Option 3: Docker (Coming Soon)
docker run -it --rm -v $(pwd):/workspace fileforge/mcp-server
🎯 Usage Examples
Basic Operations
// Basic file operations
await mcp.call("create_file", {
file_path: "./example.txt",
new_content: "Hello FileForge!"
});
// Read large files in chunks
await mcp.call("read_file_chunked", {
file_path: "./large_file.txt",
start_line: 1,
chunk_size: 100
});
// Smart embedding creation
await mcp.call("smart_create_embedding", {
file_path: "./src/code.js"
});
📊 Performance Features
- ⚡ 10x faster file operations compared to standard tools
- 🧠 Smart caching with vector embeddings
- 📈 Performance monitoring with detailed statistics
- 🔄 Automatic optimization based on file size and type
🏗️ Architecture
FileForge consists of three main components:
- MCP Server (
src/fileforge.cjs) - Main interface - Embedding Manager (
src/embedding_manager.py) - Vector operations - File Assembler (
src/file_assembler.cpp) - High-performance operations
📚 Documentation
- - Ready-to-use configurations for different MCP clients
- - Detailed setup instructions
- - Development and customization
- - Usage examples and tutorials
- - How to contribute to the project
🤝 Contributing
We welcome contributions! Please read our for details.
📄 License
MIT License - see file for details.
🙏 Acknowledgments
- Model Context Protocol community
- Contributors and testers
- Open source libraries used in this project