zrald1/README.md

Advanced Graph RAG MCP Server with file location identification, graph processing, and result summarization capabilities

# Zrald-1 MCP Server

Advanced Graph RAG MCP Server with file location identification, graph processing, and result summarization capabilities.

## Features

- **File Location Identification**: Intelligently identify and locate files based on user queries
- **Graph Processing**: Convert files into knowledge graph representations with nodes and relationships
- **Vector Search**: Semantic search across file content using vector embeddings
- **Relationship Analysis**: Analyze relationships between files based on content similarity, references, and dependencies
- **Comprehensive Summarization**: Generate detailed summaries and analytics of processed files
- **Export Capabilities**: Export graph data in multiple formats (JSON, Cypher, GraphML)

## Installation

```bash
npm install zrald-1
```

## Usage

### As a standalone MCP server

```bash
npx zrald-1
```

### As a library

```typescript
import { GraphRAGMCPServer } from 'zrald-1';

const server = new GraphRAGMCPServer();
await server.initialize();
await server.start();
```

## Available Tools

### File Processing Tools

1. **identify_files** - Identify and locate files based on search criteria
2. **process_files_to_graph** - Convert identified files into graph nodes and relationships
3. **generate_file_summary** - Generate comprehensive summaries of processed files
4. **search_file_content** - Search within file content using vector similarity
5. **analyze_file_relationships** - Analyze relationships between files
6. **export_graph_data** - Export graph data in various formats

### Vector Search Tools

7. **vdb_search** - Vector similarity search across all processed content

### Analytics Tools

8. **graph_analytics** - Get comprehensive analytics about the file graph

## Configuration

Create a `.env` file in your project root:

```env
VECTOR_DIMENSION=384
MAX_VECTOR_ELEMENTS=10000
```

## Tool Examples

### Identify Files

```json
{
  "name": "identify_files",
  "arguments": {
    "query": "typescript configuration",
    "search_paths": ["./src", "./config"],
    "file_types": [".ts", ".json"],
    "recursive": true,
    "max_results": 20
  }
}
```

### Process Files to Graph

```json
{
  "name": "process_files_to_graph",
  "arguments": {
    "file_ids": ["file-id-1", "file-id-2"],
    "create_chunks": true,
    "chunk_size": 1000,
    "chunk_overlap": 100
  }
}
```

### Generate Summary

```json
{
  "name": "generate_file_summary",
  "arguments": {
    "include_content_analysis": true,
    "include_relationships": true,
    "include_statistics": true,
    "summary_type": "comprehensive"
  }
}
```

### Search File Content

```json
{
  "name": "search_file_content",
  "arguments": {
    "query": "database connection configuration",
    "top_k": 10,
    "similarity_threshold": 0.7,
    "file_types": [".js", ".ts", ".json"]
  }
}
```

## Resources

The server provides access to several resources:

- `files://processed-files` - All processed files and metadata
- `graph://file-graph` - Knowledge graph representation
- `analytics://file-analytics` - Analytics and statistics

## Development

### Build

```bash
npm run build
```

### Development Mode

```bash
npm run dev
```

### Testing

```bash
npm test
```

## Architecture

The server consists of several key components:

- **FileProcessor**: Handles file identification, processing, and content analysis
- **VectorStore**: Manages vector embeddings and similarity search
- **GraphRAGMCPServer**: Main MCP server implementation with tool handlers

## License

MIT

## Contributing

Contributions are welcome! Please read the contributing guidelines before submitting PRs.

## Support

For issues and questions, please use the GitHub issue tracker.