| Name | mcp-vector-search JSON |
| Version |
0.4.12
JSON |
| download |
| home_page | None |
| Summary | CLI-first semantic code search with MCP integration |
| upload_time | 2025-08-22 06:42:23 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.11 |
| 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
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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
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE. |
| keywords |
code-search
mcp
semantic-search
vector-database
|
| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
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| coveralls test coverage |
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|
# MCP Vector Search
🔍 **CLI-first semantic code search with MCP integration**
[](https://badge.fury.io/py/mcp-vector-search)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
> ⚠️ **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
- **Semi-Automatic Reindexing**: Multiple strategies without daemon processes
### 🔧 **Technical Features**
- **Vector Database**: ChromaDB with connection pooling for 13.6% performance boost
- **Embedding Models**: Configurable sentence transformers
- **Smart Reindexing**: Search-triggered, Git hooks, scheduled tasks, and manual options
- **Extensible Parsers**: Plugin architecture for new languages
- **Configuration Management**: Project-specific settings
- **Production Ready**: Connection pooling, auto-indexing, comprehensive error handling
## 🚀 Quick Start
### Installation
```bash
# Install from PyPI
pip install mcp-vector-search
# Or with UV (recommended)
uv add mcp-vector-search
# Or install from source
git clone https://github.com/bobmatnyc/mcp-vector-search.git
cd mcp-vector-search
uv sync && uv pip install -e .
```
### 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"
# Setup automatic reindexing (recommended)
mcp-vector-search auto-index setup --method all
# Check project status
mcp-vector-search status
# Start file watching (auto-update index)
mcp-vector-search watch
```
### Smart CLI with "Did You Mean" Suggestions
The CLI includes intelligent command suggestions for typos:
```bash
# Typos are automatically detected and corrected
$ mcp-vector-search serach "auth"
No such command 'serach'. Did you mean 'search'?
$ mcp-vector-search indx
No such command 'indx'. Did you mean 'index'?
```
See [docs/CLI_FEATURES.md](docs/CLI_FEATURES.md) for more details.
## Versioning & Releasing
This project uses semantic versioning with an automated release workflow.
### Quick Commands
- `make version-show` - Display current version
- `make release-patch` - Create patch release
- `make publish` - Publish to PyPI
See [docs/VERSIONING_WORKFLOW.md](docs/VERSIONING_WORKFLOW.md) for complete documentation.
## 📖 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
# Reindex entire project
mcp-vector-search index reindex
# Reindex entire project (explicit)
mcp-vector-search index reindex --all
# Reindex entire project without confirmation
mcp-vector-search index reindex --force
# Reindex specific file
mcp-vector-search index reindex path/to/file.py
```
#### `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"
```
#### `auto-index` - Automatic Reindexing
```bash
# Setup all auto-indexing strategies
mcp-vector-search auto-index setup --method all
# Setup specific strategies
mcp-vector-search auto-index setup --method git-hooks
mcp-vector-search auto-index setup --method scheduled --interval 60
# Check for stale files and auto-reindex
mcp-vector-search auto-index check --auto-reindex --max-files 10
# View auto-indexing status
mcp-vector-search auto-index status
# Remove auto-indexing setup
mcp-vector-search auto-index teardown --method all
```
#### `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
```
## 🚀 Performance Features
### Connection Pooling
Automatic connection pooling provides **13.6% performance improvement** with zero configuration:
```python
# Automatically enabled for high-throughput scenarios
from mcp_vector_search.core.database import PooledChromaVectorDatabase
database = PooledChromaVectorDatabase(
max_connections=10, # Pool size
min_connections=2, # Warm connections
max_idle_time=300.0, # 5 minutes
)
```
### Semi-Automatic Reindexing
Multiple strategies to keep your index up-to-date without daemon processes:
1. **Search-Triggered**: Automatically checks for stale files during searches
2. **Git Hooks**: Triggers reindexing after commits, merges, checkouts
3. **Scheduled Tasks**: System-level cron jobs or Windows tasks
4. **Manual Checks**: On-demand via CLI commands
5. **Periodic Checker**: In-process periodic checks for long-running apps
```bash
# Setup all strategies
mcp-vector-search auto-index setup --method all
# Check status
mcp-vector-search auto-index status
```
### 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
## 🛠️ Development
### Three-Stage Development Workflow
**Stage A: Local Development & Testing**
```bash
# Setup development environment
uv sync && uv pip install -e .
# Run development tests
./scripts/dev-test.sh
# Test CLI locally
uv run mcp-vector-search version
```
**Stage B: Local Deployment Testing**
```bash
# Build and test clean deployment
./scripts/deploy-test.sh
# Test on other projects
cd ~/other-project
mcp-vector-search init && mcp-vector-search index
```
**Stage C: PyPI Publication**
```bash
# Publish to PyPI
./scripts/publish.sh
# Verify published version
pip install mcp-vector-search --upgrade
```
### Quick Reference
```bash
./scripts/workflow.sh # Show workflow overview
```
See [DEVELOPMENT.md](DEVELOPMENT.md) for detailed development instructions.
## 📚 Documentation
For comprehensive documentation, see **[CLAUDE.md](CLAUDE.md)** - the main documentation index.
### Quick Links
- **[Installation & Deployment](docs/DEPLOY.md)** - Setup and deployment guide
- **[Project Structure](docs/STRUCTURE.md)** - Architecture and file organization
- **[Contributing Guidelines](docs/developer/CONTRIBUTING.md)** - How to contribute
- **[API Reference](docs/developer/API.md)** - Internal API documentation
- **[Testing Guide](docs/developer/TESTING.md)** - Testing strategies
- **[Code Quality](docs/developer/LINTING.md)** - Linting and formatting
- **[Versioning](docs/VERSIONING.md)** - Version management
- **[Releases](docs/RELEASES.md)** - Release process
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
## 📄 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
---
**Built with ❤️ for developers who love efficient code search**
Raw data
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"description": "# MCP Vector Search\n\n\ud83d\udd0d **CLI-first semantic code search with MCP integration**\n\n[](https://badge.fury.io/py/mcp-vector-search)\n[](https://www.python.org/downloads/)\n[](https://opensource.org/licenses/MIT)\n\n> \u26a0\ufe0f **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!\n\nA 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.\n\n## \u2728 Features\n\n### \ud83d\ude80 **Core Capabilities**\n- **Semantic Search**: Find code by meaning, not just keywords\n- **AST-Aware Parsing**: Understands code structure (functions, classes, methods)\n- **Multi-Language Support**: Python, JavaScript, TypeScript (with extensible architecture)\n- **Real-time Indexing**: File watching with automatic index updates\n- **Local-First**: Complete privacy with on-device processing\n- **Zero Configuration**: Auto-detects project structure and languages\n\n### \ud83d\udee0\ufe0f **Developer Experience**\n- **CLI-First Design**: Simple commands for immediate productivity\n- **Rich Output**: Syntax highlighting, similarity scores, context\n- **Fast Performance**: Sub-second search responses, efficient indexing\n- **Modern Architecture**: Async-first, type-safe, modular design\n- **Semi-Automatic Reindexing**: Multiple strategies without daemon processes\n\n### \ud83d\udd27 **Technical Features**\n- **Vector Database**: ChromaDB with connection pooling for 13.6% performance boost\n- **Embedding Models**: Configurable sentence transformers\n- **Smart Reindexing**: Search-triggered, Git hooks, scheduled tasks, and manual options\n- **Extensible Parsers**: Plugin architecture for new languages\n- **Configuration Management**: Project-specific settings\n- **Production Ready**: Connection pooling, auto-indexing, comprehensive error handling\n\n## \ud83d\ude80 Quick Start\n\n### Installation\n\n```bash\n# Install from PyPI\npip install mcp-vector-search\n\n# Or with UV (recommended)\nuv add mcp-vector-search\n\n# Or install from source\ngit clone https://github.com/bobmatnyc/mcp-vector-search.git\ncd mcp-vector-search\nuv sync && uv pip install -e .\n```\n\n### Basic Usage\n\n```bash\n# Initialize your project\nmcp-vector-search init\n\n# Index your codebase\nmcp-vector-search index\n\n# Search your code\nmcp-vector-search search \"authentication logic\"\nmcp-vector-search search \"database connection setup\"\nmcp-vector-search search \"error handling patterns\"\n\n# Setup automatic reindexing (recommended)\nmcp-vector-search auto-index setup --method all\n\n# Check project status\nmcp-vector-search status\n\n# Start file watching (auto-update index)\nmcp-vector-search watch\n```\n\n### Smart CLI with \"Did You Mean\" Suggestions\n\nThe CLI includes intelligent command suggestions for typos:\n\n```bash\n# Typos are automatically detected and corrected\n$ mcp-vector-search serach \"auth\"\nNo such command 'serach'. Did you mean 'search'?\n\n$ mcp-vector-search indx\nNo such command 'indx'. Did you mean 'index'?\n```\n\nSee [docs/CLI_FEATURES.md](docs/CLI_FEATURES.md) for more details.\n\n## Versioning & Releasing\n\nThis project uses semantic versioning with an automated release workflow.\n\n### Quick Commands\n- `make version-show` - Display current version\n- `make release-patch` - Create patch release\n- `make publish` - Publish to PyPI\n\nSee [docs/VERSIONING_WORKFLOW.md](docs/VERSIONING_WORKFLOW.md) for complete documentation.\n\n## \ud83d\udcd6 Documentation\n\n### Commands\n\n#### `init` - Initialize Project\n```bash\n# Basic initialization\nmcp-vector-search init\n\n# Custom configuration\nmcp-vector-search init --extensions .py,.js,.ts --embedding-model sentence-transformers/all-MiniLM-L6-v2\n\n# Force re-initialization\nmcp-vector-search init --force\n```\n\n#### `index` - Index Codebase\n```bash\n# Index all files\nmcp-vector-search index\n\n# Index specific directory\nmcp-vector-search index /path/to/code\n\n# Force re-indexing\nmcp-vector-search index --force\n\n# Reindex entire project\nmcp-vector-search index reindex\n\n# Reindex entire project (explicit)\nmcp-vector-search index reindex --all\n\n# Reindex entire project without confirmation\nmcp-vector-search index reindex --force\n\n# Reindex specific file\nmcp-vector-search index reindex path/to/file.py\n```\n\n#### `search` - Semantic Search\n```bash\n# Basic search\nmcp-vector-search search \"function that handles user authentication\"\n\n# Adjust similarity threshold\nmcp-vector-search search \"database queries\" --threshold 0.7\n\n# Limit results\nmcp-vector-search search \"error handling\" --limit 10\n\n# Search in specific context\nmcp-vector-search search similar \"path/to/function.py:25\"\n```\n\n#### `auto-index` - Automatic Reindexing\n```bash\n# Setup all auto-indexing strategies\nmcp-vector-search auto-index setup --method all\n\n# Setup specific strategies\nmcp-vector-search auto-index setup --method git-hooks\nmcp-vector-search auto-index setup --method scheduled --interval 60\n\n# Check for stale files and auto-reindex\nmcp-vector-search auto-index check --auto-reindex --max-files 10\n\n# View auto-indexing status\nmcp-vector-search auto-index status\n\n# Remove auto-indexing setup\nmcp-vector-search auto-index teardown --method all\n```\n\n#### `watch` - File Watching\n```bash\n# Start watching for changes\nmcp-vector-search watch\n\n# Check watch status\nmcp-vector-search watch status\n\n# Enable/disable watching\nmcp-vector-search watch enable\nmcp-vector-search watch disable\n```\n\n#### `status` - Project Information\n```bash\n# Basic status\nmcp-vector-search status\n\n# Detailed information\nmcp-vector-search status --verbose\n```\n\n#### `config` - Configuration Management\n```bash\n# View configuration\nmcp-vector-search config show\n\n# Update settings\nmcp-vector-search config set similarity_threshold 0.8\nmcp-vector-search config set embedding_model microsoft/codebert-base\n\n# List available models\nmcp-vector-search config models\n```\n\n## \ud83d\ude80 Performance Features\n\n### Connection Pooling\nAutomatic connection pooling provides **13.6% performance improvement** with zero configuration:\n\n```python\n# Automatically enabled for high-throughput scenarios\nfrom mcp_vector_search.core.database import PooledChromaVectorDatabase\n\ndatabase = PooledChromaVectorDatabase(\n max_connections=10, # Pool size\n min_connections=2, # Warm connections\n max_idle_time=300.0, # 5 minutes\n)\n```\n\n### Semi-Automatic Reindexing\nMultiple strategies to keep your index up-to-date without daemon processes:\n\n1. **Search-Triggered**: Automatically checks for stale files during searches\n2. **Git Hooks**: Triggers reindexing after commits, merges, checkouts\n3. **Scheduled Tasks**: System-level cron jobs or Windows tasks\n4. **Manual Checks**: On-demand via CLI commands\n5. **Periodic Checker**: In-process periodic checks for long-running apps\n\n```bash\n# Setup all strategies\nmcp-vector-search auto-index setup --method all\n\n# Check status\nmcp-vector-search auto-index status\n```\n\n### Configuration\n\nProjects are configured via `.mcp-vector-search/config.json`:\n\n```json\n{\n \"project_root\": \"/path/to/project\",\n \"file_extensions\": [\".py\", \".js\", \".ts\"],\n \"embedding_model\": \"sentence-transformers/all-MiniLM-L6-v2\",\n \"similarity_threshold\": 0.75,\n \"languages\": [\"python\", \"javascript\", \"typescript\"],\n \"watch_files\": true,\n \"cache_embeddings\": true\n}\n```\n\n## \ud83c\udfd7\ufe0f Architecture\n\n### Core Components\n\n- **Parser Registry**: Extensible system for language-specific parsing\n- **Semantic Indexer**: Efficient code chunking and embedding generation\n- **Vector Database**: ChromaDB integration for similarity search\n- **File Watcher**: Real-time monitoring and incremental updates\n- **CLI Interface**: Rich, user-friendly command-line experience\n\n### Supported Languages\n\n| Language | Status | Features |\n|------------|--------|----------|\n| Python | \u2705 Full | Functions, classes, methods, docstrings |\n| JavaScript | \u2705 Full | Functions, classes, JSDoc, ES6+ syntax |\n| TypeScript | \u2705 Full | Interfaces, types, generics, decorators |\n| Java | \ud83d\udd04 Planned | Classes, methods, annotations |\n| Go | \ud83d\udd04 Planned | Functions, structs, interfaces |\n| Rust | \ud83d\udd04 Planned | Functions, structs, traits |\n\n## \ud83e\udd1d Contributing\n\nWe welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.\n\n### Development Setup\n\n```bash\n# Clone the repository\ngit clone https://github.com/bobmatnyc/mcp-vector-search.git\ncd mcp-vector-search\n\n# Install dependencies with UV\nuv sync\n\n# Install in development mode\nuv pip install -e .\n\n# Run tests\nuv run pytest\n\n# Run linting\nuv run ruff check\nuv run mypy src/\n```\n\n### Adding Language Support\n\n1. Create a new parser in `src/mcp_vector_search/parsers/`\n2. Extend the `BaseParser` class\n3. Register the parser in `parsers/registry.py`\n4. Add tests and documentation\n\n## \ud83d\udcca Performance\n\n- **Indexing Speed**: ~1000 files/minute (typical Python project)\n- **Search Latency**: <100ms for most queries\n- **Memory Usage**: ~50MB baseline + ~1MB per 1000 code chunks\n- **Storage**: ~1KB per code chunk (compressed embeddings)\n\n## \u26a0\ufe0f Known Limitations (Alpha)\n\n- **Tree-sitter Integration**: Currently using regex fallback parsing (Tree-sitter setup needs improvement)\n- **Search Relevance**: Embedding model may need tuning for code-specific queries\n- **Error Handling**: Some edge cases may not be gracefully handled\n- **Documentation**: API documentation is minimal\n- **Testing**: Limited test coverage, needs real-world validation\n\n## \ud83d\ude4f Feedback Needed\n\nWe're actively seeking feedback on:\n\n- **Search Quality**: How relevant are the search results for your codebase?\n- **Performance**: How does indexing and search speed feel in practice?\n- **Usability**: Is the CLI interface intuitive and helpful?\n- **Language Support**: Which languages would you like to see added next?\n- **Features**: What functionality is missing for your workflow?\n\nPlease [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!\n\n## \ud83d\udd2e Roadmap\n\n### v0.0.x: Alpha (Current) \ud83d\udd04\n- [x] Core CLI interface\n- [x] Python/JS/TS parsing\n- [x] ChromaDB integration\n- [x] File watching\n- [x] Basic search functionality\n- [ ] Real-world testing and feedback\n- [ ] Bug fixes and stability improvements\n- [ ] Performance optimizations\n\n### v0.1.x: Beta \ud83d\udd2e\n- [ ] Advanced search modes (contextual, similar code)\n- [ ] Additional language support (Java, Go, Rust)\n- [ ] Configuration improvements\n- [ ] Comprehensive testing suite\n- [ ] Documentation improvements\n\n### v1.0.x: Stable \ud83d\udd2e\n- [ ] MCP server implementation\n- [ ] IDE extensions (VS Code, JetBrains)\n- [ ] Git integration\n- [ ] Team collaboration features\n- [ ] Production-ready performance\n\n## \ud83d\udee0\ufe0f Development\n\n### Three-Stage Development Workflow\n\n**Stage A: Local Development & Testing**\n```bash\n# Setup development environment\nuv sync && uv pip install -e .\n\n# Run development tests\n./scripts/dev-test.sh\n\n# Test CLI locally\nuv run mcp-vector-search version\n```\n\n**Stage B: Local Deployment Testing**\n```bash\n# Build and test clean deployment\n./scripts/deploy-test.sh\n\n# Test on other projects\ncd ~/other-project\nmcp-vector-search init && mcp-vector-search index\n```\n\n**Stage C: PyPI Publication**\n```bash\n# Publish to PyPI\n./scripts/publish.sh\n\n# Verify published version\npip install mcp-vector-search --upgrade\n```\n\n### Quick Reference\n```bash\n./scripts/workflow.sh # Show workflow overview\n```\n\nSee [DEVELOPMENT.md](DEVELOPMENT.md) for detailed development instructions.\n\n## \ud83d\udcda Documentation\n\nFor comprehensive documentation, see **[CLAUDE.md](CLAUDE.md)** - the main documentation index.\n\n### Quick Links\n- **[Installation & Deployment](docs/DEPLOY.md)** - Setup and deployment guide\n- **[Project Structure](docs/STRUCTURE.md)** - Architecture and file organization\n- **[Contributing Guidelines](docs/developer/CONTRIBUTING.md)** - How to contribute\n- **[API Reference](docs/developer/API.md)** - Internal API documentation\n- **[Testing Guide](docs/developer/TESTING.md)** - Testing strategies\n- **[Code Quality](docs/developer/LINTING.md)** - Linting and formatting\n- **[Versioning](docs/VERSIONING.md)** - Version management\n- **[Releases](docs/RELEASES.md)** - Release process\n\n## \ud83e\udd1d Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.\n\n## \ud83d\udcc4 License\n\nMIT License - see [LICENSE](LICENSE) file for details.\n\n## \ud83d\ude4f Acknowledgments\n\n- [ChromaDB](https://github.com/chroma-core/chroma) for vector database\n- [Tree-sitter](https://tree-sitter.github.io/) for parsing infrastructure\n- [Sentence Transformers](https://www.sbert.net/) for embeddings\n- [Typer](https://typer.tiangolo.com/) for CLI framework\n- [Rich](https://rich.readthedocs.io/) for beautiful terminal output\n\n---\n\n**Built with \u2764\ufe0f for developers who love efficient code search**\n",
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"license": "MIT License\n \n Copyright (c) 2024 Robert Matsuoka\n \n Permission is hereby granted, free of charge, to any person obtaining a copy\n of this software and associated documentation files (the \"Software\"), to deal\n in the Software without restriction, including without limitation the rights\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n copies of the Software, and to permit persons to whom the Software is\n furnished to do so, subject to the following conditions:\n \n The above copyright notice and this permission notice shall be included in all\n copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n SOFTWARE.",
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