Metadata-Version: 2.4
Name: mcp-vector-search
Version: 0.0.3
Summary: CLI-first semantic code search with MCP integration
Project-URL: Homepage, https://github.com/bobmatnyc/mcp-vector-search
Project-URL: Documentation, https://mcp-vector-search.readthedocs.io
Project-URL: Repository, https://github.com/bobmatnyc/mcp-vector-search
Project-URL: Bug Tracker, https://github.com/bobmatnyc/mcp-vector-search/issues
Author-email: Robert Matsuoka <bobmatnyc@gmail.com>
License: MIT License
        
        Copyright (c) 2024 Robert Matsuoka
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
License-File: LICENSE
Keywords: code-search,mcp,semantic-search,vector-database
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Software Development :: Code Generators
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.11
Requires-Dist: aiofiles>=23.0.0
Requires-Dist: chromadb>=0.5.0
Requires-Dist: httpx>=0.25.0
Requires-Dist: loguru>=0.7.0
Requires-Dist: pydantic-settings>=2.1.0
Requires-Dist: pydantic>=2.5.0
Requires-Dist: rich>=13.0.0
Requires-Dist: sentence-transformers>=2.2.2
Requires-Dist: tree-sitter-languages>=1.8.0
Requires-Dist: tree-sitter>=0.20.1
Requires-Dist: typer>=0.9.0
Requires-Dist: watchdog>=3.0.0
Description-Content-Type: text/markdown

# MCP Vector Search

🔍 **CLI-first semantic code search with MCP integration**

> ⚠️ **Alpha Release (v0.0.3)**: This is an early-stage project under active development. Expect breaking changes and rough edges. Feedback and contributions are welcome!

A modern, fast, and intelligent code search tool that understands your codebase through semantic analysis and AST parsing. Built with Python, powered by ChromaDB, and designed for developer productivity.

## ✨ Features

### 🚀 **Core Capabilities**
- **Semantic Search**: Find code by meaning, not just keywords
- **AST-Aware Parsing**: Understands code structure (functions, classes, methods)
- **Multi-Language Support**: Python, JavaScript, TypeScript (with extensible architecture)
- **Real-time Indexing**: File watching with automatic index updates
- **Local-First**: Complete privacy with on-device processing
- **Zero Configuration**: Auto-detects project structure and languages

### 🛠️ **Developer Experience**
- **CLI-First Design**: Simple commands for immediate productivity
- **Rich Output**: Syntax highlighting, similarity scores, context
- **Fast Performance**: Sub-second search responses, efficient indexing
- **Modern Architecture**: Async-first, type-safe, modular design

### 🔧 **Technical Features**
- **Vector Database**: ChromaDB for efficient similarity search
- **Embedding Models**: Configurable sentence transformers
- **Incremental Updates**: Smart file watching and re-indexing
- **Extensible Parsers**: Plugin architecture for new languages
- **Configuration Management**: Project-specific settings

## 🚀 Quick Start

### Installation

```bash
# Install with UV (recommended)
uv add mcp-vector-search

# Or with pip
pip install mcp-vector-search
```

### Basic Usage

```bash
# Initialize your project
mcp-vector-search init

# Index your codebase
mcp-vector-search index

# Search your code
mcp-vector-search search "authentication logic"
mcp-vector-search search "database connection setup"
mcp-vector-search search "error handling patterns"

# Check project status
mcp-vector-search status

# Start file watching (auto-update index)
mcp-vector-search watch
```

## 📖 Documentation

### Commands

#### `init` - Initialize Project
```bash
# Basic initialization
mcp-vector-search init

# Custom configuration
mcp-vector-search init --extensions .py,.js,.ts --embedding-model sentence-transformers/all-MiniLM-L6-v2

# Force re-initialization
mcp-vector-search init --force
```

#### `index` - Index Codebase
```bash
# Index all files
mcp-vector-search index

# Index specific directory
mcp-vector-search index /path/to/code

# Force re-indexing
mcp-vector-search index --force
```

#### `search` - Semantic Search
```bash
# Basic search
mcp-vector-search search "function that handles user authentication"

# Adjust similarity threshold
mcp-vector-search search "database queries" --threshold 0.7

# Limit results
mcp-vector-search search "error handling" --limit 10

# Search in specific context
mcp-vector-search search similar "path/to/function.py:25"
```

#### `watch` - File Watching
```bash
# Start watching for changes
mcp-vector-search watch

# Check watch status
mcp-vector-search watch status

# Enable/disable watching
mcp-vector-search watch enable
mcp-vector-search watch disable
```

#### `status` - Project Information
```bash
# Basic status
mcp-vector-search status

# Detailed information
mcp-vector-search status --verbose
```

#### `config` - Configuration Management
```bash
# View configuration
mcp-vector-search config show

# Update settings
mcp-vector-search config set similarity_threshold 0.8
mcp-vector-search config set embedding_model microsoft/codebert-base

# List available models
mcp-vector-search config models
```

### Configuration

Projects are configured via `.mcp-vector-search/config.json`:

```json
{
  "project_root": "/path/to/project",
  "file_extensions": [".py", ".js", ".ts"],
  "embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
  "similarity_threshold": 0.75,
  "languages": ["python", "javascript", "typescript"],
  "watch_files": true,
  "cache_embeddings": true
}
```

## 🏗️ Architecture

### Core Components

- **Parser Registry**: Extensible system for language-specific parsing
- **Semantic Indexer**: Efficient code chunking and embedding generation
- **Vector Database**: ChromaDB integration for similarity search
- **File Watcher**: Real-time monitoring and incremental updates
- **CLI Interface**: Rich, user-friendly command-line experience

### Supported Languages

| Language   | Status | Features |
|------------|--------|----------|
| Python     | ✅ Full | Functions, classes, methods, docstrings |
| JavaScript | ✅ Full | Functions, classes, JSDoc, ES6+ syntax |
| TypeScript | ✅ Full | Interfaces, types, generics, decorators |
| Java       | 🔄 Planned | Classes, methods, annotations |
| Go         | 🔄 Planned | Functions, structs, interfaces |
| Rust       | 🔄 Planned | Functions, structs, traits |

## 🤝 Contributing

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.

### Development Setup

```bash
# Clone the repository
git clone https://github.com/bobmatnyc/mcp-vector-search.git
cd mcp-vector-search

# Install dependencies with UV
uv sync

# Install in development mode
uv pip install -e .

# Run tests
uv run pytest

# Run linting
uv run ruff check
uv run mypy src/
```

### Adding Language Support

1. Create a new parser in `src/mcp_vector_search/parsers/`
2. Extend the `BaseParser` class
3. Register the parser in `parsers/registry.py`
4. Add tests and documentation

## 📊 Performance

- **Indexing Speed**: ~1000 files/minute (typical Python project)
- **Search Latency**: <100ms for most queries
- **Memory Usage**: ~50MB baseline + ~1MB per 1000 code chunks
- **Storage**: ~1KB per code chunk (compressed embeddings)

## ⚠️ Known Limitations (Alpha)

- **Tree-sitter Integration**: Currently using regex fallback parsing (Tree-sitter setup needs improvement)
- **Search Relevance**: Embedding model may need tuning for code-specific queries
- **Error Handling**: Some edge cases may not be gracefully handled
- **Documentation**: API documentation is minimal
- **Testing**: Limited test coverage, needs real-world validation

## 🙏 Feedback Needed

We're actively seeking feedback on:

- **Search Quality**: How relevant are the search results for your codebase?
- **Performance**: How does indexing and search speed feel in practice?
- **Usability**: Is the CLI interface intuitive and helpful?
- **Language Support**: Which languages would you like to see added next?
- **Features**: What functionality is missing for your workflow?

Please [open an issue](https://github.com/bobmatnyc/mcp-vector-search/issues) or start a [discussion](https://github.com/bobmatnyc/mcp-vector-search/discussions) to share your experience!

## 🔮 Roadmap

### v0.0.x: Alpha (Current) 🔄
- [x] Core CLI interface
- [x] Python/JS/TS parsing
- [x] ChromaDB integration
- [x] File watching
- [x] Basic search functionality
- [ ] Real-world testing and feedback
- [ ] Bug fixes and stability improvements
- [ ] Performance optimizations

### v0.1.x: Beta 🔮
- [ ] Advanced search modes (contextual, similar code)
- [ ] Additional language support (Java, Go, Rust)
- [ ] Configuration improvements
- [ ] Comprehensive testing suite
- [ ] Documentation improvements

### v1.0.x: Stable 🔮
- [ ] MCP server implementation
- [ ] IDE extensions (VS Code, JetBrains)
- [ ] Git integration
- [ ] Team collaboration features
- [ ] Production-ready performance

## 📄 License

MIT License - see [LICENSE](LICENSE) file for details.

## 🙏 Acknowledgments

- [ChromaDB](https://github.com/chroma-core/chroma) for vector database
- [Tree-sitter](https://tree-sitter.github.io/) for parsing infrastructure
- [Sentence Transformers](https://www.sbert.net/) for embeddings
- [Typer](https://typer.tiangolo.com/) for CLI framework
- [Rich](https://rich.readthedocs.io/) for beautiful terminal output

---

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