[{"_1":2,"_477":-5,"_478":-5},"loaderData",{"_3":4,"_22":23,"_317":318},"root",{"_5":6,"_7":8},"toasts",[],"visitor",{"_9":10,"_11":12},"viewportWidth",1280,"visitorSession",{"_13":14,"_16":17,"_18":-5,"_19":20,"_21":-5},"attributes",[15],"bot","id",17782814,"membership","referenceId","0199bf5f-ca2b-7322-a5a4-336805538485","userAccount","routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_24":25,"_66":-5,"_67":26,"_27":68,"_232":233,"_315":316},"availableLocales",[26,38,45,52,59],{"_27":28,"_31":35,"_36":37},"mcpServer",{"_29":30,"_31":32,"_33":34},"description","An MCP server implementation that helps Claude remember and learn from programming errors by storing, retrieving, and finding similar errors with full context.","name","Tribal Knowledge Service","readme","# Tribal - Knowledge Service\n\nTribal is an MCP (Model Context Protocol) server implementation for error knowledge tracking and retrieval. It provides both REST API and native MCP interfaces for integration with tools like Claude Code and Cline.\n\n## Features\n\n- Store and retrieve error records with full context\n- Vector similarity search using ChromaDB\n- REST API (FastAPI) and native MCP interfaces\n- JWT authentication with API keys\n- Local storage (ChromaDB) and AWS integration\n- Docker-compose deployment\n- CLI client integration\n\n## Overview\n\nTribal helps Claude remember and learn from programming errors. When you start a Claude Code session, Tribal is automatically available through MCP without additional imports.\n\nClaude will:\n1. Store programming errors and solutions\n2. Search for similar errors when you encounter problems\n3. Build a knowledge base specific to your coding patterns\n\n## Packaging and Installing Tribal with uv\n\n### Prerequisites\n\n- Python 3.12+\n- uv package manager (recommended)\n\n### Build and Install Steps\n\n#### Option 1: Direct installation with uv\n\nThe simplest approach is to install directly from the current directory:\n\n```bash\n# From the project root directory\ncd /path/to/tribal\n\n# Install using uv\nuv pip install .\n```\n\n#### Option 2: Development Installation\n\nFor development work where you want changes to be immediately reflected:\n\n```bash\n# From the project root directory\ncd /path/to/tribal\n\n# Install in development mode\nuv pip install -e .\n```\n\n#### Option 3: Build the package first\n\nIf you want to build a distributable package:\n\n```bash\n# Make sure you're in the project root directory\ncd /path/to/tribal\n\n# Install the build package if needed\nuv pip install build\n\n# Build the package\npython -m build\n\n# This creates distribution files in the dist/ directory\n# Now install the wheel file\nuv pip install dist/tribal-0.1.0-py3-none-any.whl\n```\n\n#### Option 4: Using the `uv tool install` command\n\nYou can also use the tool installation approach:\n\n```bash\n# Install as a global tool\ncd /path/to/tribal\nuv tool install .\n\n# Or install in development mode\nuv tool install -e .\n```\n\n### Verification\n\nAfter installation, verify that the tool is properly installed:\n\n```bash\n# Check the installation\nwhich tribal\n\n# Check the version\ntribal version\n```\n\n### Integration with Claude\n\nAfter installation, you can integrate with Claude:\n\n```bash\n# Add Tribal to Claude Code\nclaude mcp add tribal --launch \"tribal\"\n\n# Verify the configuration\nclaude mcp list\n\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n```\n\n## Usage\n\n### Available MCP Tools\n\nTribal provides these MCP tools:\n\n1. `add_error` - Create new error record (POST /errors)\n2. `get_error` - Retrieve error by UUID (GET /errors/{id})\n3. `update_error` - Modify existing error (PUT /errors/{id})\n4. `delete_error` - Remove error record (DELETE /errors/{id})\n5. `search_errors` - Find errors by criteria (GET /errors)\n6. `find_similar` - Semantic similarity search (GET /errors/similar)\n7. `get_token` - Obtain JWT token (POST /token)\n\n### Example Usage with Claude\n\nWhen Claude encounters an error:\n```\nI'll track this error and look for similar problems in our knowledge base.\n```\n\nWhen Claude finds a solution:\n```\nI've found a solution! I'll store this in our knowledge base for next time.\n```\n\n### Commands for Claude\n\nYou can ask Claude to:\n- \"Look for similar errors in our Tribal knowledge base\"\n- \"Store this solution to our error database\"\n- \"Check if we've seen this error before\"\n\n### Running the Server\n\n#### Using the tribal command\n\n```bash\n# Run the server\ntribal\n\n# Get help\ntribal help\n\n# Show version\ntribal version\n\n# Run with options\ntribal server --port 5000 --auto-port\n```\n\n#### Using Python modules\n\n```bash\n# Run the Tribal server\npython -m mcp_server_tribal.mcp_app\n\n# Run the FastAPI backend server\npython -m mcp_server_tribal.app\n```\n\n#### Using legacy entry points\n\n```bash\n# Legacy MCP server\nmcp-server\n\n# Legacy FastAPI server\nmcp-api\n```\n\n### Command-line Options\n\n```bash\n# Development mode with auto-reload\nmcp-api --reload\nmcp-server --reload\n\n# Custom port\nmcp-api --port 8080\nmcp-server --port 5000\n\n# Auto port selection\nmcp-api --auto-port\nmcp-server --auto-port\n```\n\nThe FastAPI server will be available at http://localhost:8000 with API documentation at /docs.\nThe MCP server will be available at http://localhost:5000 for Claude and other MCP-compatible LLMs.\n\n### Environment Variables\n\n#### FastAPI Server\n- `PERSIST_DIRECTORY`: ChromaDB storage path (default: \"./chroma_db\")\n- `API_KEY`: Authentication key (default: \"dev-api-key\")\n- `SECRET_KEY`: JWT signing key (default: \"insecure-dev-key-change-in-production\")\n- `REQUIRE_AUTH`: Authentication requirement (default: \"false\")\n- `PORT`: Server port (default: 8000)\n\n#### MCP Server\n- `MCP_API_URL`: FastAPI server URL (default: \"http://localhost:8000\")\n- `MCP_PORT`: MCP server port (default: 5000)\n- `MCP_HOST`: Host to bind to (default: \"0.0.0.0\")\n- `API_KEY`: FastAPI access key (default: \"dev-api-key\")\n- `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_S3_BUCKET`: For AWS integration\n\n### API Endpoints\n\n- `POST /errors`: Create new error record\n- `GET /errors/{error_id}`: Get error by ID\n- `PUT /errors/{error_id}`: Update error record\n- `DELETE /errors/{error_id}`: Delete error\n- `GET /errors`: Search errors by criteria\n- `GET /errors/similar`: Find similar errors\n- `POST /token`: Get authentication token\n\n### Using the Client\n\n```bash\n# Add a new error record\nmcp-client --action add --error-type ImportError --language python --error-message \"No module named 'requests'\" --solution-description \"Install requests\" --solution-explanation \"You need to install the requests package\"\n\n# Get an error by ID\nmcp-client --action get --id \n\n# Search for errors\nmcp-client --action search --error-type ImportError --language python\n\n# Find similar errors\nmcp-client --action similar --query \"ModuleNotFoundError: No module named 'pandas'\"\n```\n\n### How It Works\n\n1. Tribal uses ChromaDB to store error records and solutions\n2. When Claude encounters an error, it sends the error details to Tribal\n3. Tribal vectorizes the error and searches for similar ones\n4. Claude gets back relevant solutions to suggest\n5. New solutions are stored for future reference\n\n## Development\n\n### Running Tests\n\n```bash\npytest\npytest tests/path_to_test.py::test_name # For specific tests\n```\n\n### Linting and Type Checking\n\n```bash\nruff check .\nmypy .\nblack .\n```\n\n### GitHub Workflow\n\nThis project uses GitHub Actions for continuous integration and deployment. The workflow automatically runs tests, linting, and type checking on push to main and pull requests.\n\n#### Workflow Steps\n\n1. **Test**: Runs linting, type checking, and unit tests\n - Uses Python 3.12\n - Installs dependencies with uv\n - Runs ruff, black, mypy, and pytest\n\n2. **Build and Publish**: Builds and publishes the package to PyPI\n - Triggered only on push to main branch\n - Uses Python's build system\n - Publishes to PyPI using twine\n\n#### Testing Locally\n\nYou can test the GitHub workflow locally using the provided script:\n\n```bash\n# Make the script executable\nchmod +x scripts/test-workflow.sh\n\n# Run the workflow locally\n./scripts/test-workflow.sh\n```\n\nThis script simulates the GitHub workflow steps on your local machine:\n- Checks Python version (3.12 recommended)\n- Installs dependencies using uv\n- Runs linting with ruff\n- Checks formatting with black\n- Runs type checking with mypy\n- Runs tests with pytest\n- Builds the package\n\nNote: The script skips the publishing step for local testing.\n\n### Project Structure\n\n```\ntribal/\n├── src/\n│ ├── mcp_server_tribal/ # Core package\n│ │ ├── api/ # FastAPI endpoints\n│ │ ├── cli/ # Command-line interface\n│ │ ├── models/ # Pydantic models\n│ │ ├── services/ # Service layer\n│ │ │ ├── aws/ # AWS integrations\n│ │ │ └── chroma_storage.py # ChromaDB implementation\n│ │ └── utils/ # Utility functions\n│ └── examples/ # Example usage code\n├── tests/ # pytest test suite\n├── docker-compose.yml # Docker production setup\n├── pyproject.toml # Project configuration\n├── VERSIONING.md # Versioning strategy documentation\n├── CHANGELOG.md # Version history\n├── .bumpversion.cfg # Version bumping configuration\n└── README.md # Project documentation\n```\n\n## Versioning\n\nTribal follows [Semantic Versioning](https://semver.org/). See [VERSIONING.md](VERSIONING.md) for complete details about:\n\n- Version numbering (MAJOR.MINOR.PATCH)\n- Schema versioning for database compatibility\n- Branch naming conventions\n- Release and hotfix procedures\n\nCheck the version with:\n\n```bash\n# Display version information\ntribal version\n```\n\n### Managing Dependencies\n\n```bash\n# Add a dependency\nuv pip add \n\n# Add a development dependency\nuv pip add \n\n# Update dependencies\nuv pip sync requirements.txt requirements-dev.txt\n```\n\n## Deployment\n\n### Docker Deployment\n\n```bash\n# Build and start containers\ndocker-compose up -d --build\n\n# View logs\ndocker-compose logs -f\n\n# Stop containers\ndocker-compose down\n\n# With custom environment variables\nAPI_PORT=8080 MCP_PORT=5000 REQUIRE_AUTH=true API_KEY=your-secret-key docker-start\n```\n\n### Claude for Desktop Integration\n\n#### Option 1: Let Claude for Desktop Launch the Server\n\n1. Open `~/Library/Application Support/Claude/claude_desktop_config.json`\n\n2. Add the MCP server configuration (assumes Tribal tool is already installed):\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"launchCommand\": \"tribal\"\n }\n ]\n }\n ```\n\n3. Restart Claude for Desktop\n\n#### Option 2: Connect to Running Docker Container\n\n1. Start the container:\n ```bash\n cd /path/to/tribal\n docker-start\n ```\n\n2. Configure Claude for Desktop:\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"url\": \"http://localhost:5000\"\n }\n ]\n }\n ```\n\n### Claude Code CLI Integration\n\n```bash\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n\n# For directly launched server\nclaude mcp add tribal --launch \"tribal\"\n\n# Test the connection\nclaude mcp list\nclaude mcp test tribal\n```\n\n## Troubleshooting\n\n1. Verify Tribal installation: `which tribal`\n2. Check configuration: `claude mcp list`\n3. Test server status: `tribal status`\n4. Look for error messages in the Claude output\n5. Check the database directory exists and has proper permissions\n\n## Cloud Deployment\n\nThe project includes placeholder implementations for AWS services:\n- `S3Storage`: For storing error records in Amazon S3\n- `DynamoDBStorage`: For using DynamoDB as the database\n\n## License\n\n[MIT License](LICENSE)\n","English","tag","en-US",{"_27":39,"_31":43,"_36":44},{"_29":40,"_31":41,"_33":42},"Una implementación de servidor MCP que ayuda a Claude a recordar y aprender de los errores de programación almacenando, recuperando y encontrando errores similares con contexto completo.","Servicio de Conocimiento Tribal","# Tribal - Servicio de Conocimiento\n\nTribal es una implementación de servidor MCP (Protocolo de Contexto de Modelo) para el seguimiento y la recuperación de conocimiento de errores. Ofrece API REST e interfaces MCP nativas para la integración con herramientas como Claude Code y Cline.\n\n## Características\n\n* Almacenar y recuperar registros de errores con contexto completo\n* Búsqueda de similitud de vectores usando ChromaDB\n* API REST (FastAPI) e interfaces MCP nativas\n* Autenticación JWT con claves API\n* Almacenamiento local (ChromaDB) e integración con AWS\n* Implementación de Docker-compose\n* Integración del cliente CLI\n\n## Descripción general\n\nTribal ayuda a Claude a recordar y aprender de los errores de programación. Al iniciar una sesión de Claude Code, Tribal está disponible automáticamente a través de MCP sin necesidad de importaciones adicionales.\n\nClaude querrá:\n\n1. Errores de programación de la tienda y soluciones\n2. Busque errores similares cuando encuentre problemas\n3. Cree una base de conocimientos específica para sus patrones de codificación\n\n## Embalaje e instalación de Tribal con uv\n\n### Prerrequisitos\n\n* Python 3.12+\n* Gestor de paquetes uv (recomendado)\n\n### Pasos de construcción e instalación\n\n#### Opción 1: Instalación directa con uv\n\nEl enfoque más simple es instalar directamente desde el directorio actual:\n\n```bash\n# From the project root directory\ncd /path/to/tribal\n\n# Install using uv\nuv pip install .\n```\n\n#### Opción 2: Instalación de desarrollo\n\nPara trabajos de desarrollo donde desea que los cambios se reflejen inmediatamente:\n\n```bash\n# From the project root directory\ncd /path/to/tribal\n\n# Install in development mode\nuv pip install -e .\n```\n\n#### Opción 3: Construya el paquete primero\n\nSi desea crear un paquete distribuible:\n\n```bash\n# Make sure you're in the project root directory\ncd /path/to/tribal\n\n# Install the build package if needed\nuv pip install build\n\n# Build the package\npython -m build\n\n# This creates distribution files in the dist/ directory\n# Now install the wheel file\nuv pip install dist/tribal-0.1.0-py3-none-any.whl\n```\n\n#### Opción 4: Usar el comando `uv tool install`\n\nTambién puede utilizar el método de instalación de herramientas:\n\n```bash\n# Install as a global tool\ncd /path/to/tribal\nuv tool install .\n\n# Or install in development mode\nuv tool install -e .\n```\n\n### Verificación\n\nDespués de la instalación, verifique que la herramienta esté correctamente instalada:\n\n```bash\n# Check the installation\nwhich tribal\n\n# Check the version\ntribal version\n```\n\n### Integración con Claude\n\nDespués de la instalación, puedes integrarlo con Claude:\n\n```bash\n# Add Tribal to Claude Code\nclaude mcp add tribal --launch \"tribal\"\n\n# Verify the configuration\nclaude mcp list\n\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n```\n\n## Uso\n\n### Herramientas MCP disponibles\n\nTribal proporciona estas herramientas MCP:\n\n1. `add_error` - Crea un nuevo registro de error (POST/errors)\n2. `get_error` - Recuperar error por UUID (GET /errors/{id})\n3. `update_error` - Modificar el error existente (PUT /errors/{id})\n4. `delete_error` - Eliminar registro de error (DELETE /errors/{id})\n5. `search_errors` - Buscar errores por criterios (GET /errors)\n6. `find_similar` - Búsqueda de similitud semántica (GET /errors/similar)\n7. `get_token` - Obtener el token JWT (POST /token)\n\n### Ejemplo de uso con Claude\n\nCuando Claude encuentra un error:\n\n```\nI'll track this error and look for similar problems in our knowledge base.\n```\n\nCuando Claude encuentra una solución:\n\n```\nI've found a solution! I'll store this in our knowledge base for next time.\n```\n\n### Órdenes para Claude\n\nPuedes pedirle a Claude que:\n\n* Busque errores similares en nuestra base de conocimientos tribales.\n* \"Guarde esta solución en nuestra base de datos de errores\"\n* \"Comprobar si hemos visto este error antes\"\n\n### Ejecución del servidor\n\n#### Usando el comando tribal\n\n```bash\n# Run the server\ntribal\n\n# Get help\ntribal help\n\n# Show version\ntribal version\n\n# Run with options\ntribal server --port 5000 --auto-port\n```\n\n#### Uso de módulos de Python\n\n```bash\n# Run the Tribal server\npython -m mcp_server_tribal.mcp_app\n\n# Run the FastAPI backend server\npython -m mcp_server_tribal.app\n```\n\n#### Uso de puntos de entrada heredados\n\n```bash\n# Legacy MCP server\nmcp-server\n\n# Legacy FastAPI server\nmcp-api\n```\n\n### Opciones de la línea de comandos\n\n```bash\n# Development mode with auto-reload\nmcp-api --reload\nmcp-server --reload\n\n# Custom port\nmcp-api --port 8080\nmcp-server --port 5000\n\n# Auto port selection\nmcp-api --auto-port\nmcp-server --auto-port\n```\n\nEl servidor FastAPI estará disponible en con la documentación de la API en /docs. El servidor MCP estará disponible en para Claude y otros LLM compatibles con MCP.\n\n### Variables de entorno\n\n#### Servidor FastAPI\n\n* `PERSIST_DIRECTORY` : Ruta de almacenamiento de ChromaDB (predeterminado: \"./chroma\\_db\")\n* `API_KEY` : Clave de autenticación (predeterminada: \"dev-api-key\")\n* `SECRET_KEY` : Clave de firma JWT (valor predeterminado: \"insecure-dev-key-change-in-production\")\n* `REQUIRE_AUTH` : Requisito de autenticación (predeterminado: \"falso\")\n* `PORT` : Puerto del servidor (predeterminado: 8000)\n\n#### Servidor MCP\n\n* `MCP_API_URL` : URL del servidor FastAPI (predeterminado: \" \")\n* `MCP_PORT` : puerto del servidor MCP (predeterminado: 5000)\n* `MCP_HOST` : Host al que vincular (predeterminado: \"0.0.0.0\")\n* `API_KEY` : Clave de acceso de FastAPI (predeterminada: \"dev-api-key\")\n* `AWS_ACCESS_KEY_ID` , `AWS_SECRET_ACCESS_KEY` , `AWS_S3_BUCKET` : para la integración con AWS\n\n### Puntos finales de API\n\n* `POST /errors` : Crear nuevo registro de errores\n* `GET /errors/{error_id}` : Obtener el error por ID\n* `PUT /errors/{error_id}` : Actualizar registro de errores\n* `DELETE /errors/{error_id}` : Eliminar error\n* `GET /errors` : Buscar errores por criterios\n* `GET /errors/similar` : Encuentra errores similares\n* `POST /token` : Obtener el token de autenticación\n\n### Uso del cliente\n\n```bash\n# Add a new error record\nmcp-client --action add --error-type ImportError --language python --error-message \"No module named 'requests'\" --solution-description \"Install requests\" --solution-explanation \"You need to install the requests package\"\n\n# Get an error by ID\nmcp-client --action get --id \n\n# Search for errors\nmcp-client --action search --error-type ImportError --language python\n\n# Find similar errors\nmcp-client --action similar --query \"ModuleNotFoundError: No module named 'pandas'\"\n```\n\n### Cómo funciona\n\n1. Tribal utiliza ChromaDB para almacenar registros de errores y soluciones\n2. Cuando Claude encuentra un error, envía los detalles del error a Tribal.\n3. Tribal vectoriza el error y busca otros similares\n4. Claude recupera soluciones relevantes para sugerir\n5. Las nuevas soluciones se almacenan para futuras referencias.\n\n## Desarrollo\n\n### Ejecución de pruebas\n\n```bash\npytest\npytest tests/path_to_test.py::test_name # For specific tests\n```\n\n### Comprobación de tipo y desbastado\n\n```bash\nruff check .\nmypy .\nblack .\n```\n\n### Flujo de trabajo de GitHub\n\nEste proyecto utiliza GitHub Actions para la integración y el despliegue continuos. El flujo de trabajo ejecuta automáticamente pruebas, análisis de errores y verificación de tipos en las solicitudes de inserción y extracción.\n\n#### Pasos del flujo de trabajo\n\n1. **Prueba** : ejecuta pelusa, verificación de tipos y pruebas unitarias\n\n * Utiliza Python 3.12\n * Instala dependencias con uv\n * Ejecuta ruff, black, mypy y pytest\n\n2. **Construir y publicar** : construye y publica el paquete en PyPI\n\n * Se activa solo al enviar a la rama principal\n * Utiliza el sistema de compilación de Python\n * Publica en PyPI usando twine\n\n#### Pruebas locales\n\nPuede probar el flujo de trabajo de GitHub localmente utilizando el script proporcionado:\n\n```bash\n# Make the script executable\nchmod +x scripts/test-workflow.sh\n\n# Run the workflow locally\n./scripts/test-workflow.sh\n```\n\nEste script simula los pasos del flujo de trabajo de GitHub en su máquina local:\n\n* Comprueba la versión de Python (se recomienda 3.12)\n* Instala dependencias usando uv\n* Se corre con pelusa\n* Comprueba el formato con negro\n* Ejecuta la verificación de tipos con mypy\n* Ejecuta pruebas con pytest\n* Construye el paquete\n\nNota: el script omite el paso de publicación para las pruebas locales.\n\n### Estructura del proyecto\n\n```\ntribal/\n├── src/\n│ ├── mcp_server_tribal/ # Core package\n│ │ ├── api/ # FastAPI endpoints\n│ │ ├── cli/ # Command-line interface\n│ │ ├── models/ # Pydantic models\n│ │ ├── services/ # Service layer\n│ │ │ ├── aws/ # AWS integrations\n│ │ │ └── chroma_storage.py # ChromaDB implementation\n│ │ └── utils/ # Utility functions\n│ └── examples/ # Example usage code\n├── tests/ # pytest test suite\n├── docker-compose.yml # Docker production setup\n├── pyproject.toml # Project configuration\n├── VERSIONING.md # Versioning strategy documentation\n├── CHANGELOG.md # Version history\n├── .bumpversion.cfg # Version bumping configuration\n└── README.md # Project documentation\n```\n\n## Control de versiones\n\nTribal sigue [el control de versiones semántico](https://semver.org/) . Consulte [VERSIONING.md](VERSIONING.md) para obtener más información sobre:\n\n* Numeración de versiones (MAYOR.MINOR.PATCH)\n* Control de versiones del esquema para compatibilidad con bases de datos\n* Convenciones de nombres de ramas\n* Procedimientos de lanzamiento y revisión\n\nCompruebe la versión con:\n\n```bash\n# Display version information\ntribal version\n```\n\n### Gestión de dependencias\n\n```bash\n# Add a dependency\nuv pip add \n\n# Add a development dependency\nuv pip add \n\n# Update dependencies\nuv pip sync requirements.txt requirements-dev.txt\n```\n\n## Despliegue\n\n### Implementación de Docker\n\n```bash\n# Build and start containers\ndocker-compose up -d --build\n\n# View logs\ndocker-compose logs -f\n\n# Stop containers\ndocker-compose down\n\n# With custom environment variables\nAPI_PORT=8080 MCP_PORT=5000 REQUIRE_AUTH=true API_KEY=your-secret-key docker-start\n```\n\n### Claude para integración de escritorio\n\n#### Opción 1: Dejar que Claude for Desktop inicie el servidor\n\n1. Abra `~/Library/Application Support/Claude/claude_desktop_config.json`\n\n2. Agregue la configuración del servidor MCP (supone que la herramienta Tribal ya está instalada):\n\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"launchCommand\": \"tribal\"\n }\n ]\n }\n ```\n\n3. Reiniciar Claude para escritorio\n\n#### Opción 2: Conectarse al contenedor Docker en ejecución\n\n1. Iniciar el contenedor:\n\n ```bash\n cd /path/to/tribal\n docker-start\n ```\n\n2. Configurar Claude para escritorio:\n\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"url\": \"http://localhost:5000\"\n }\n ]\n }\n ```\n\n### Integración CLI de Claude Code\n\n```bash\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n\n# For directly launched server\nclaude mcp add tribal --launch \"tribal\"\n\n# Test the connection\nclaude mcp list\nclaude mcp test tribal\n```\n\n## Solución de problemas\n\n1. Verificar la instalación tribal: `which tribal`\n2. Comprobar configuración: `claude mcp list`\n3. Estado del servidor de prueba: `tribal status`\n4. Busque mensajes de error en la salida de Claude\n5. Verifique que el directorio de la base de datos exista y tenga los permisos adecuados\n\n## Implementación en la nube\n\nEl proyecto incluye implementaciones de marcador de posición para los servicios de AWS:\n\n* `S3Storage` : para almacenar registros de errores en Amazon S3\n* `DynamoDBStorage` : para utilizar DynamoDB como base de datos\n\n## Licencia\n\n[Licencia MIT](LICENSE)","Spanish","es-ES",{"_27":46,"_31":50,"_36":51},{"_29":47,"_31":48,"_33":49},"完全なコンテキストで類似のエラーを保存、取得、検索することで、Claude がプログラミングエラーを記憶して学習できるようにする MCP サーバー実装。","部族知識サービス","# 部族 - 知識サービス\n\nTribalは、エラーナレッジの追跡と取得のためのMCP（Model Context Protocol）サーバー実装です。Claude CodeやClineなどのツールとの統合のために、REST APIとネイティブMCPインターフェースの両方を提供します。\n\n## 特徴\n\n* 完全なコンテキストでエラーレコードを保存および取得します\n* ChromaDB を使用したベクトル類似性検索\n* REST API (FastAPI) とネイティブ MCP インターフェース\n* APIキーを使用したJWT認証\n* ローカルストレージ（ChromaDB）とAWS統合\n* Docker-compose デプロイメント\n* CLIクライアント統合\n\n## 概要\n\nTribalは、Claudeがプログラミングエラーを記憶し、学習するのに役立ちます。Claude Codeセッションを開始すると、追加のインポートなしでTribalがMCPを通じて自動的に利用可能になります。\n\nクロードは次のことを行います:\n\n1. ストアプログラミングエラーと解決策\n2. 問題が発生した場合に類似のエラーを検索する\n3. コーディングパターンに特化した知識ベースを構築する\n\n## UVを使用したTribalのパッケージ化とインストール\n\n### 前提条件\n\n* Python 3.12以上\n* uv パッケージマネージャー (推奨)\n\n### ビルドとインストールの手順\n\n#### オプション1：UVによる直接設置\n\n最も簡単な方法は、現在のディレクトリから直接インストールすることです。\n\n```bash\n# From the project root directory\ncd /path/to/tribal\n\n# Install using uv\nuv pip install .\n```\n\n#### オプション2: 開発インストール\n\n変更をすぐに反映させたい開発作業の場合:\n\n```bash\n# From the project root directory\ncd /path/to/tribal\n\n# Install in development mode\nuv pip install -e .\n```\n\n#### オプション3: 最初にパッケージをビルドする\n\n配布可能なパッケージをビルドする場合:\n\n```bash\n# Make sure you're in the project root directory\ncd /path/to/tribal\n\n# Install the build package if needed\nuv pip install build\n\n# Build the package\npython -m build\n\n# This creates distribution files in the dist/ directory\n# Now install the wheel file\nuv pip install dist/tribal-0.1.0-py3-none-any.whl\n```\n\n#### オプション4: `uv tool install`コマンドを使用する\n\nツールのインストール方法を使用することもできます。\n\n```bash\n# Install as a global tool\ncd /path/to/tribal\nuv tool install .\n\n# Or install in development mode\nuv tool install -e .\n```\n\n### 検証\n\nインストール後、ツールが正しくインストールされていることを確認します。\n\n```bash\n# Check the installation\nwhich tribal\n\n# Check the version\ntribal version\n```\n\n### クロードとの統合\n\nインストール後、Claude と統合できます。\n\n```bash\n# Add Tribal to Claude Code\nclaude mcp add tribal --launch \"tribal\"\n\n# Verify the configuration\nclaude mcp list\n\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n```\n\n## 使用法\n\n### 利用可能なMCPツール\n\nTribal は次の MCP ツールを提供します。\n\n1. `add_error` - 新しいエラーレコードを作成する (POST /errors)\n2. `get_error` - UUIDでエラーを取得する (GET /errors/{id})\n3. `update_error` - 既存のエラーを変更する (PUT /errors/{id})\n4. `delete_error` - エラーレコードを削除する (DELETE /errors/{id})\n5. `search_errors` - 条件でエラーを検索する (GET /errors)\n6. `find_similar` - 意味的類似性検索 (GET /errors/similar)\n7. `get_token` - JWTトークンを取得する（POST /token）\n\n### クロードとの使用例\n\nクロードがエラーに遭遇した場合:\n\n```\nI'll track this error and look for similar problems in our knowledge base.\n```\n\nクロードが解決策を見つけたとき:\n\n```\nI've found a solution! I'll store this in our knowledge base for next time.\n```\n\n### クロードへのコマンド\n\nクロードに次のことを依頼できます。\n\n* 「部族の知識ベースで同様のエラーを探してください」\n* 「このソリューションをエラーデータベースに保存します」\n* 「このエラーが以前に発生したかどうかを確認してください」\n\n### サーバーの実行\n\n#### 部族の命令を使う\n\n```bash\n# Run the server\ntribal\n\n# Get help\ntribal help\n\n# Show version\ntribal version\n\n# Run with options\ntribal server --port 5000 --auto-port\n```\n\n#### Pythonモジュールの使用\n\n```bash\n# Run the Tribal server\npython -m mcp_server_tribal.mcp_app\n\n# Run the FastAPI backend server\npython -m mcp_server_tribal.app\n```\n\n#### レガシーエントリポイントの使用\n\n```bash\n# Legacy MCP server\nmcp-server\n\n# Legacy FastAPI server\nmcp-api\n```\n\n### コマンドラインオプション\n\n```bash\n# Development mode with auto-reload\nmcp-api --reload\nmcp-server --reload\n\n# Custom port\nmcp-api --port 8080\nmcp-server --port 5000\n\n# Auto port selection\nmcp-api --auto-port\nmcp-server --auto-port\n```\n\nFastAPIサーバーはで利用可能で、APIドキュメントは/docsにあります。Claudeやその他のMCP対応LLM用のMCPサーバーはで利用可能になります。\n\n### 環境変数\n\n#### FastAPIサーバー\n\n* `PERSIST_DIRECTORY` : ChromaDB ストレージパス (デフォルト: \"./chroma\\_db\")\n* `API_KEY` : 認証キー（デフォルト: \"dev-api-key\")\n* `SECRET_KEY` : JWT署名キー（デフォルト: \"insecure-dev-key-change-in-production\")\n* `REQUIRE_AUTH` : 認証要件（デフォルト: \"false\"）\n* `PORT` : サーバーポート（デフォルト: 8000）\n\n#### MCPサーバー\n\n* `MCP_API_URL` : FastAPI サーバーの URL (デフォルト: \" \")\n* `MCP_PORT` : MCPサーバポート（デフォルト: 5000）\n* `MCP_HOST` : バインドするホスト（デフォルト: \"0.0.0.0\")\n* `API_KEY` : FastAPI アクセスキー (デフォルト: \"dev-api-key\")\n* `AWS_ACCESS_KEY_ID` 、 `AWS_SECRET_ACCESS_KEY` 、 `AWS_S3_BUCKET` : AWS統合用\n\n### APIエンドポイント\n\n* `POST /errors` : 新しいエラーレコードを作成する\n* `GET /errors/{error_id}` : IDでエラーを取得する\n* `PUT /errors/{error_id}` : エラーレコードを更新する\n* `DELETE /errors/{error_id}` : エラーを削除\n* `GET /errors` : 条件でエラーを検索する\n* `GET /errors/similar` : 類似のエラーを検索する\n* `POST /token` : 認証トークンを取得する\n\n### クライアントの使用\n\n```bash\n# Add a new error record\nmcp-client --action add --error-type ImportError --language python --error-message \"No module named 'requests'\" --solution-description \"Install requests\" --solution-explanation \"You need to install the requests package\"\n\n# Get an error by ID\nmcp-client --action get --id \n\n# Search for errors\nmcp-client --action search --error-type ImportError --language python\n\n# Find similar errors\nmcp-client --action similar --query \"ModuleNotFoundError: No module named 'pandas'\"\n```\n\n### 仕組み\n\n1. TribalはChromaDBを使用してエラー記録と解決策を保存します\n2. クロードがエラーに遭遇すると、エラーの詳細をTribalに送信します。\n3. トライバルはエラーをベクトル化し、類似のエラーを検索します\n4. クロードは適切な解決策を提案します\n5. 新しいソリューションは将来の参照用に保存されます\n\n## 発達\n\n### テストの実行\n\n```bash\npytest\npytest tests/path_to_test.py::test_name # For specific tests\n```\n\n### リンティングと型チェック\n\n```bash\nruff check .\nmypy .\nblack .\n```\n\n### GitHubワークフロー\n\nこのプロジェクトでは、継続的インテグレーションとデプロイメントにGitHub Actionsを使用しています。このワークフローは、メインへのプッシュとプルリクエスト時に、テスト、リンティング、型チェックを自動的に実行します。\n\n#### ワークフローの手順\n\n1. **テスト**: リンティング、型チェック、ユニットテストを実行します\n\n * Python 3.12 を使用\n * uvで依存関係をインストールします\n * ruff、black、mypy、pytest を実行\n\n2. **ビルドと公開**: パッケージをビルドしてPyPIに公開します\n\n * メインブランチへのプッシュ時にのみトリガーされます\n * Pythonのビルドシステムを使用する\n * twineを使用してPyPIに公開する\n\n#### ローカルテスト\n\n提供されているスクリプトを使用して、GitHub ワークフローをローカルでテストできます。\n\n```bash\n# Make the script executable\nchmod +x scripts/test-workflow.sh\n\n# Run the workflow locally\n./scripts/test-workflow.sh\n```\n\nこのスクリプトは、ローカルマシン上で GitHub ワークフローステップをシミュレートします。\n\n* Pythonのバージョンをチェックします（3.12を推奨）\n* uvを使用して依存関係をインストールします\n* 毛羽立ちとひだのある走り\n* 黒でフォーマットをチェック\n* mypyで型チェックを実行する\n* pytestでテストを実行する\n* パッケージをビルドする\n\n注: スクリプトは、ローカルテストの公開手順をスキップします。\n\n### プロジェクト構造\n\n```\ntribal/\n├── src/\n│ ├── mcp_server_tribal/ # Core package\n│ │ ├── api/ # FastAPI endpoints\n│ │ ├── cli/ # Command-line interface\n│ │ ├── models/ # Pydantic models\n│ │ ├── services/ # Service layer\n│ │ │ ├── aws/ # AWS integrations\n│ │ │ └── chroma_storage.py # ChromaDB implementation\n│ │ └── utils/ # Utility functions\n│ └── examples/ # Example usage code\n├── tests/ # pytest test suite\n├── docker-compose.yml # Docker production setup\n├── pyproject.toml # Project configuration\n├── VERSIONING.md # Versioning strategy documentation\n├── CHANGELOG.md # Version history\n├── .bumpversion.cfg # Version bumping configuration\n└── README.md # Project documentation\n```\n\n## バージョン管理\n\nTribalは[セマンティックバージョニング](https://semver.org/)に準拠しています。詳細については[VERSIONING.mdを](VERSIONING.md)ご覧ください。\n\n* バージョン番号 (MAJOR.MINOR.PATCH)\n* データベース互換性のためのスキーマのバージョン管理\n* ブランチの命名規則\n* リリースとホットフィックスの手順\n\nバージョンを確認するには以下を実行します:\n\n```bash\n# Display version information\ntribal version\n```\n\n### 依存関係の管理\n\n```bash\n# Add a dependency\nuv pip add \n\n# Add a development dependency\nuv pip add \n\n# Update dependencies\nuv pip sync requirements.txt requirements-dev.txt\n```\n\n## 展開\n\n### Docker デプロイメント\n\n```bash\n# Build and start containers\ndocker-compose up -d --build\n\n# View logs\ndocker-compose logs -f\n\n# Stop containers\ndocker-compose down\n\n# With custom environment variables\nAPI_PORT=8080 MCP_PORT=5000 REQUIRE_AUTH=true API_KEY=your-secret-key docker-start\n```\n\n### デスクトップ統合のクロード\n\n#### オプション1: Claude for Desktopでサーバーを起動する\n\n1. `~/Library/Application Support/Claude/claude_desktop_config.json`開きます。\n\n2. MCP サーバー構成を追加します (Tribal ツールがすでにインストールされていることを前提としています)。\n\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"launchCommand\": \"tribal\"\n }\n ]\n }\n ```\n\n3. デスクトップ版のClaudeを再起動する\n\n#### オプション2: 実行中のDockerコンテナに接続する\n\n1. コンテナを起動します。\n\n ```bash\n cd /path/to/tribal\n docker-start\n ```\n\n2. Claude をデスクトップ用に設定する:\n\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"url\": \"http://localhost:5000\"\n }\n ]\n }\n ```\n\n### Claude Code CLI 統合\n\n```bash\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n\n# For directly launched server\nclaude mcp add tribal --launch \"tribal\"\n\n# Test the connection\nclaude mcp list\nclaude mcp test tribal\n```\n\n## トラブルシューティング\n\n1. 部族のインストールを確認する: `which tribal`\n2. 設定を確認してください: `claude mcp list`\n3. テストサーバーのステータス: `tribal status`\n4. Claudeの出力でエラーメッセージを探す\n5. データベースディレクトリが存在し、適切な権限があることを確認してください\n\n## クラウド展開\n\nこのプロジェクトには、AWS サービスのプレースホルダー実装が含まれています。\n\n* `S3Storage` : Amazon S3にエラーレコードを保存する\n* `DynamoDBStorage` : データベースとして DynamoDB を使用する場合\n\n## ライセンス\n\n[MITライセンス](LICENSE)","Japanese","ja-JP",{"_27":53,"_31":57,"_36":58},{"_29":54,"_31":55,"_33":56},"클로드가 프로그래밍 오류를 기억하고 이를 통해 학습할 수 있도록 돕는 MCP 서버 구현으로, 전체 맥락을 고려하여 유사한 오류를 저장, 검색 및 찾아냅니다.","부족 지식 서비스","# 부족 - 지식 서비스\n\nTribal은 오류 지식 추적 및 검색을 위한 MCP(Model Context Protocol) 서버 구현입니다. Claude Code 및 Cline과 같은 도구와의 통합을 위해 REST API와 기본 MCP 인터페이스를 모두 제공합니다.\n\n## 특징\n\n* 전체 컨텍스트를 사용하여 오류 레코드를 저장하고 검색합니다.\n* ChromaDB를 이용한 벡터 유사성 검색\n* REST API(FastAPI) 및 기본 MCP 인터페이스\n* API 키를 사용한 JWT 인증\n* 로컬 스토리지(ChromaDB) 및 AWS 통합\n* Docker-compose 배포\n* CLI 클라이언트 통합\n\n## 개요\n\nTribal은 Claude가 프로그래밍 오류를 기억하고 이를 통해 학습할 수 있도록 도와줍니다. Claude Code 세션을 시작하면 추가 가져오기 없이 MCP를 통해 Tribal을 자동으로 사용할 수 있습니다.\n\n클로드는 다음을 할 것입니다:\n\n1. 스토어 프로그래밍 오류 및 솔루션\n2. 문제가 발생하면 유사한 오류를 검색하세요\n3. 귀하의 코딩 패턴에 맞는 지식 기반을 구축하세요\n\n## UV를 이용한 Tribal 패키징 및 설치\n\n### 필수 조건\n\n* 파이썬 3.12+\n* uv 패키지 관리자(추천)\n\n### 빌드 및 설치 단계\n\n#### 옵션 1: UV를 이용한 직접 설치\n\n가장 간단한 방법은 현재 디렉토리에서 직접 설치하는 것입니다.\n\n지엑스피1\n\n#### 옵션 2: 개발 설치\n\n변경 사항을 즉시 반영하려는 개발 작업의 경우:\n\n```bash\n# From the project root directory\ncd /path/to/tribal\n\n# Install in development mode\nuv pip install -e .\n```\n\n#### 옵션 3: 먼저 패키지를 빌드하세요\n\n배포 가능한 패키지를 빌드하려면 다음을 수행하세요.\n\n```bash\n# Make sure you're in the project root directory\ncd /path/to/tribal\n\n# Install the build package if needed\nuv pip install build\n\n# Build the package\npython -m build\n\n# This creates distribution files in the dist/ directory\n# Now install the wheel file\nuv pip install dist/tribal-0.1.0-py3-none-any.whl\n```\n\n#### 옵션 4: `uv tool install` 명령 사용\n\n도구 설치 방법을 사용할 수도 있습니다.\n\n```bash\n# Install as a global tool\ncd /path/to/tribal\nuv tool install .\n\n# Or install in development mode\nuv tool install -e .\n```\n\n### 확인\n\n설치 후 도구가 제대로 설치되었는지 확인하세요.\n\n```bash\n# Check the installation\nwhich tribal\n\n# Check the version\ntribal version\n```\n\n### Claude와의 통합\n\n설치 후 Claude와 통합할 수 있습니다.\n\n```bash\n# Add Tribal to Claude Code\nclaude mcp add tribal --launch \"tribal\"\n\n# Verify the configuration\nclaude mcp list\n\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n```\n\n## 용법\n\n### 사용 가능한 MCP 도구\n\nTribal은 다음과 같은 MCP 도구를 제공합니다.\n\n1. `add_error` - 새로운 오류 레코드 생성(POST /errors)\n2. `get_error` - UUID로 오류 검색(GET /errors/{id})\n3. `update_error` - 기존 오류 수정(PUT /errors/{id})\n4. `delete_error` - 오류 레코드 제거(DELETE /errors/{id})\n5. `search_errors` - 기준에 따라 오류 찾기(GET /errors)\n6. `find_similar` - 의미적 유사성 검색(GET /errors/similar)\n7. `get_token` - JWT 토큰 얻기(POST /token)\n\n### Claude를 사용한 예시 사용\n\n클로드가 오류를 발견했을 때:\n\n```\nI'll track this error and look for similar problems in our knowledge base.\n```\n\n클로드가 해결책을 찾았을 때:\n\n```\nI've found a solution! I'll store this in our knowledge base for next time.\n```\n\n### 클로드에 대한 명령\n\nClaude에게 다음을 요청할 수 있습니다.\n\n* \"우리 부족 지식 기반에서 유사한 오류를 찾아보세요\"\n* \"이 솔루션을 오류 데이터베이스에 저장하세요\"\n* \"이 오류가 이전에 발생했는지 확인하세요\"\n\n### 서버 실행\n\n#### 부족 명령 사용\n\n```bash\n# Run the server\ntribal\n\n# Get help\ntribal help\n\n# Show version\ntribal version\n\n# Run with options\ntribal server --port 5000 --auto-port\n```\n\n#### Python 모듈 사용\n\n```bash\n# Run the Tribal server\npython -m mcp_server_tribal.mcp_app\n\n# Run the FastAPI backend server\npython -m mcp_server_tribal.app\n```\n\n#### 레거시 진입점 사용\n\n```bash\n# Legacy MCP server\nmcp-server\n\n# Legacy FastAPI server\nmcp-api\n```\n\n### 명령줄 옵션\n\n```bash\n# Development mode with auto-reload\nmcp-api --reload\nmcp-server --reload\n\n# Custom port\nmcp-api --port 8080\nmcp-server --port 5000\n\n# Auto port selection\nmcp-api --auto-port\nmcp-server --auto-port\n```\n\nFastAPI 서버는 에서 사용할 수 있으며, API 문서는 /docs에서 확인할 수 있습니다. Claude 및 기타 MCP 호환 LLM의 경우 MCP 서버는 에서 사용할 수 있습니다.\n\n### 환경 변수\n\n#### FastAPI 서버\n\n* `PERSIST_DIRECTORY` : ChromaDB 저장 경로(기본값: \"./chroma\\_db\")\n* `API_KEY` : 인증 키(기본값: \"dev-api-key\")\n* `SECRET_KEY` : JWT 서명 키(기본값: \"insecure-dev-key-change-in-production\")\n* `REQUIRE_AUTH` : 인증 요구 사항(기본값: \"false\")\n* `PORT` : 서버 포트(기본값: 8000)\n\n#### MCP 서버\n\n* `MCP_API_URL` : FastAPI 서버 URL(기본값: \" \")\n* `MCP_PORT` : MCP 서버 포트(기본값: 5000)\n* `MCP_HOST` : 바인딩할 호스트(기본값: \"0.0.0.0\")\n* `API_KEY` : FastAPI 액세스 키(기본값: \"dev-api-key\")\n* `AWS_ACCESS_KEY_ID` , `AWS_SECRET_ACCESS_KEY` , `AWS_S3_BUCKET` : AWS 통합을 위한\n\n### API 엔드포인트\n\n* `POST /errors` : 새로운 오류 레코드를 생성합니다.\n* `GET /errors/{error_id}` : ID로 오류 가져오기\n* `PUT /errors/{error_id}` : 오류 레코드 업데이트\n* `DELETE /errors/{error_id}` : 오류 삭제\n* `GET /errors` : 기준으로 오류 검색\n* `GET /errors/similar` : 유사한 오류 찾기\n* `POST /token` : 인증 토큰 받기\n\n### 클라이언트 사용\n\n```bash\n# Add a new error record\nmcp-client --action add --error-type ImportError --language python --error-message \"No module named 'requests'\" --solution-description \"Install requests\" --solution-explanation \"You need to install the requests package\"\n\n# Get an error by ID\nmcp-client --action get --id \n\n# Search for errors\nmcp-client --action search --error-type ImportError --language python\n\n# Find similar errors\nmcp-client --action similar --query \"ModuleNotFoundError: No module named 'pandas'\"\n```\n\n### 작동 원리\n\n1. Tribal은 ChromaDB를 사용하여 오류 레코드와 솔루션을 저장합니다.\n2. Claude가 오류를 발견하면 오류 세부 정보를 Tribal로 전송합니다.\n3. Tribal은 오류를 벡터화하고 유사한 오류를 검색합니다.\n4. Claude는 제안할 관련 솔루션을 다시 가져옵니다.\n5. 새로운 솔루션은 향후 참조를 위해 저장됩니다.\n\n## 개발\n\n### 테스트 실행\n\n```bash\npytest\npytest tests/path_to_test.py::test_name # For specific tests\n```\n\n### 린팅 및 유형 검사\n\n```bash\nruff check .\nmypy .\nblack .\n```\n\n### GitHub 워크플로\n\n이 프로젝트는 지속적인 통합 및 배포를 위해 GitHub Actions를 사용합니다. 워크플로는 메인 리퀘스트 및 풀 리퀘스트에 대한 푸시, 린팅, 유형 검사를 자동으로 실행합니다.\n\n#### 워크플로 단계\n\n1. **테스트** : 린팅, 유형 검사 및 단위 테스트를 실행합니다.\n\n * Python 3.12를 사용합니다\n * uv로 종속성을 설치합니다\n * ruff, black, mypy 및 pytest를 실행합니다.\n\n2. **빌드 및 게시** : 패키지를 빌드하고 PyPI에 게시합니다.\n\n * 메인 브랜치에 푸시할 때만 트리거됨\n * Python의 빌드 시스템을 사용합니다\n * twine을 사용하여 PyPI에 게시합니다.\n\n#### 로컬 테스트\n\n제공된 스크립트를 사용하여 GitHub 워크플로를 로컬로 테스트할 수 있습니다.\n\n```bash\n# Make the script executable\nchmod +x scripts/test-workflow.sh\n\n# Run the workflow locally\n./scripts/test-workflow.sh\n```\n\n이 스크립트는 로컬 머신에서 GitHub 워크플로 단계를 시뮬레이션합니다.\n\n* Python 버전 확인(3.12 권장)\n* uv를 사용하여 종속성을 설치합니다.\n* 러프와 함께 린팅을 실행합니다.\n* 검은색으로 서식을 확인합니다.\n* mypy로 유형 검사를 실행합니다.\n* pytest로 테스트를 실행합니다\n* 패키지를 빌드합니다\n\n참고: 스크립트는 로컬 테스트를 위해 게시 단계를 건너뜁니다.\n\n### 프로젝트 구조\n\n```\ntribal/\n├── src/\n│ ├── mcp_server_tribal/ # Core package\n│ │ ├── api/ # FastAPI endpoints\n│ │ ├── cli/ # Command-line interface\n│ │ ├── models/ # Pydantic models\n│ │ ├── services/ # Service layer\n│ │ │ ├── aws/ # AWS integrations\n│ │ │ └── chroma_storage.py # ChromaDB implementation\n│ │ └── utils/ # Utility functions\n│ └── examples/ # Example usage code\n├── tests/ # pytest test suite\n├── docker-compose.yml # Docker production setup\n├── pyproject.toml # Project configuration\n├── VERSIONING.md # Versioning strategy documentation\n├── CHANGELOG.md # Version history\n├── .bumpversion.cfg # Version bumping configuration\n└── README.md # Project documentation\n```\n\n## 버전 관리\n\nTribal은 [의미적 버전 관리(Semantic Versioning)를](https://semver.org/) 따릅니다. 자세한 내용은 [VERSIONING.md를](VERSIONING.md) 참조하세요.\n\n* 버전 번호(MAJOR.MINOR.PATCH)\n* 데이터베이스 호환성을 위한 스키마 버전 관리\n* 지점 명명 규칙\n* 릴리스 및 핫픽스 절차\n\n다음 버전으로 확인하세요:\n\n```bash\n# Display version information\ntribal version\n```\n\n### 종속성 관리\n\n```bash\n# Add a dependency\nuv pip add \n\n# Add a development dependency\nuv pip add \n\n# Update dependencies\nuv pip sync requirements.txt requirements-dev.txt\n```\n\n## 전개\n\n### 도커 배포\n\n```bash\n# Build and start containers\ndocker-compose up -d --build\n\n# View logs\ndocker-compose logs -f\n\n# Stop containers\ndocker-compose down\n\n# With custom environment variables\nAPI_PORT=8080 MCP_PORT=5000 REQUIRE_AUTH=true API_KEY=your-secret-key docker-start\n```\n\n### 데스크톱 통합을 위한 Claude\n\n#### 옵션 1: 데스크톱용 Claude가 서버를 시작하도록 합니다.\n\n1. `~/Library/Application Support/Claude/claude_desktop_config.json` 엽니다.\n\n2. MCP 서버 구성을 추가합니다(Tribal 도구가 이미 설치되어 있다고 가정):\n\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"launchCommand\": \"tribal\"\n }\n ]\n }\n ```\n\n3. 데스크톱용 Claude를 다시 시작하세요\n\n#### 옵션 2: 실행 중인 Docker 컨테이너에 연결\n\n1. 컨테이너를 시작합니다.\n\n ```bash\n cd /path/to/tribal\n docker-start\n ```\n\n2. 데스크톱에 Claude 구성:\n\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"url\": \"http://localhost:5000\"\n }\n ]\n }\n ```\n\n### Claude Code CLI 통합\n\n```bash\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n\n# For directly launched server\nclaude mcp add tribal --launch \"tribal\"\n\n# Test the connection\nclaude mcp list\nclaude mcp test tribal\n```\n\n## 문제 해결\n\n1. 부족 설치 확인: `which tribal`\n2. 구성 확인: `claude mcp list`\n3. 테스트 서버 상태: `tribal status`\n4. Claude 출력에서 오류 메시지를 찾으세요.\n5. 데이터베이스 디렉토리가 존재하고 적절한 권한이 있는지 확인하세요.\n\n## 클라우드 배포\n\n이 프로젝트에는 AWS 서비스에 대한 플레이스홀더 구현이 포함되어 있습니다.\n\n* `S3Storage` : Amazon S3에 오류 레코드를 저장하기 위한 저장소\n* `DynamoDBStorage` : DynamoDB를 데이터베이스로 사용하기 위한 것입니다.\n\n## 특허\n\n[MIT 라이센스](LICENSE)","Korean","ko-KR",{"_27":60,"_31":64,"_36":65},{"_29":61,"_31":62,"_33":63},"MCP 服务器实现通过存储、检索和查找具有完整上下文的类似错误来帮助 Claude 记住编程错误并从中学习。","部落知识服务","# 部落 - 知识服务\n\nTribal 是一个用于错误知识跟踪和检索的 MCP（模型上下文协议）服务器实现。它提供 REST API 和原生 MCP 接口，可与 Claude Code 和 Cline 等工具集成。\n\n## 特征\n\n* 存储和检索具有完整上下文的错误记录\n* 使用 ChromaDB 进行向量相似性搜索\n* REST API（FastAPI）和原生 MCP 接口\n* 使用 API 密钥进行 JWT 身份验证\n* 本地存储（ChromaDB）和 AWS 集成\n* Docker-compose部署\n* CLI 客户端集成\n\n## 概述\n\nTribal 帮助 Claude 记住编程错误并从中学习。当您启动 Claude Code 会话时，Tribal 会自动通过 MCP 启动，无需额外导入。\n\n克劳德将：\n\n1. 商店编程错误和解决方案\n2. 遇到问题时搜索类似错误\n3. 构建特定于您的编码模式的知识库\n\n## 使用 uv 打包并安装 Tribal\n\n### 先决条件\n\n* Python 3.12+\n* uv 包管理器（推荐）\n\n### 构建和安装步骤\n\n#### 选项 1：直接使用 uv 安装\n\n最简单的方法是直接从当前目录安装：\n\n```bash\n# From the project root directory\ncd /path/to/tribal\n\n# Install using uv\nuv pip install .\n```\n\n#### 选项 2：开发安装\n\n对于希望立即反映更改的开发工作：\n\n```bash\n# From the project root directory\ncd /path/to/tribal\n\n# Install in development mode\nuv pip install -e .\n```\n\n#### 选项 3：首先构建包\n\n如果您想构建可分发的包：\n\n```bash\n# Make sure you're in the project root directory\ncd /path/to/tribal\n\n# Install the build package if needed\nuv pip install build\n\n# Build the package\npython -m build\n\n# This creates distribution files in the dist/ directory\n# Now install the wheel file\nuv pip install dist/tribal-0.1.0-py3-none-any.whl\n```\n\n#### 选项 4：使用`uv tool install`命令\n\n您也可以使用工具安装方法：\n\n```bash\n# Install as a global tool\ncd /path/to/tribal\nuv tool install .\n\n# Or install in development mode\nuv tool install -e .\n```\n\n### 确认\n\n安装后，验证该工具是否正确安装：\n\n```bash\n# Check the installation\nwhich tribal\n\n# Check the version\ntribal version\n```\n\n### 与克劳德的整合\n\n安装完成后，即可与Claude集成：\n\n```bash\n# Add Tribal to Claude Code\nclaude mcp add tribal --launch \"tribal\"\n\n# Verify the configuration\nclaude mcp list\n\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n```\n\n## 用法\n\n### 可用的 MCP 工具\n\nTribal 提供以下 MCP 工具：\n\n1. `add_error` - 创建新的错误记录 (POST /errors)\n2. `get_error` - 通过 UUID 检索错误（GET /errors/{id}）\n3. `update_error` - 修改现有错误 (PUT /errors/{id})\n4. `delete_error` - 删除错误记录 (DELETE /errors/{id})\n5. `search_errors` - 根据条件查找错误 (GET /errors)\n6. `find_similar` - 语义相似性搜索（GET /errors/similar）\n7. `get_token` - 获取 JWT 令牌 (POST /token)\n\n### Claude 的示例用法\n\n当克劳德遇到错误时：\n\n```\nI'll track this error and look for similar problems in our knowledge base.\n```\n\n当克劳德找到解决方案时：\n\n```\nI've found a solution! I'll store this in our knowledge base for next time.\n```\n\n### 克劳德的命令\n\n您可以要求 Claude：\n\n* “在我们的部落知识库中查找类似的错误”\n* “将此解决方案存储到我们的错误数据库中”\n* “检查我们之前是否见过这个错误”\n\n### 运行服务器\n\n#### 使用部落命令\n\n```bash\n# Run the server\ntribal\n\n# Get help\ntribal help\n\n# Show version\ntribal version\n\n# Run with options\ntribal server --port 5000 --auto-port\n```\n\n#### 使用 Python 模块\n\n```bash\n# Run the Tribal server\npython -m mcp_server_tribal.mcp_app\n\n# Run the FastAPI backend server\npython -m mcp_server_tribal.app\n```\n\n#### 使用旧式入口点\n\n```bash\n# Legacy MCP server\nmcp-server\n\n# Legacy FastAPI server\nmcp-api\n```\n\n### 命令行选项\n\n```bash\n# Development mode with auto-reload\nmcp-api --reload\nmcp-server --reload\n\n# Custom port\nmcp-api --port 8080\nmcp-server --port 5000\n\n# Auto port selection\nmcp-api --auto-port\nmcp-server --auto-port\n```\n\nFastAPI 服务器的地址为，API 文档位于 /docs。MCP 服务器的地址为[http://localhost:5000，](http://localhost:5000)适用于 Claude 和其他兼容 MCP 的 LLM。\n\n### 环境变量\n\n#### FastAPI 服务器\n\n* `PERSIST_DIRECTORY` ：ChromaDB存储路径（默认值：“./chroma\\_db”）\n* `API_KEY` ：身份验证密钥（默认值：“dev-api-key”）\n* `SECRET_KEY` ：JWT 签名密钥（默认值：“insecure-dev-key-change-in-production”）\n* `REQUIRE_AUTH` ：身份验证要求（默认值：“false”）\n* `PORT` ：服务器端口（默认值：8000）\n\n#### MCP 服务器\n\n* `MCP_API_URL` ：FastAPI 服务器 URL（默认值：“ ”）\n* `MCP_PORT` ：MCP 服务器端口（默认值：5000）\n* `MCP_HOST` ：绑定到的主机（默认值：“0.0.0.0”）\n* `API_KEY` ：FastAPI 访问密钥（默认值：“dev-api-key”）\n* `AWS_ACCESS_KEY_ID` 、 `AWS_SECRET_ACCESS_KEY` 、 `AWS_S3_BUCKET` ：用于 AWS 集成\n\n### API 端点\n\n* `POST /errors` ：创建新的错误记录\n* `GET /errors/{error_id}` ：通过 ID 获取错误\n* `PUT /errors/{error_id}` ：更新错误记录\n* `DELETE /errors/{error_id}` ：删除错误\n* `GET /errors` ：按条件搜索错误\n* `GET /errors/similar` ：查找类似的错误\n* `POST /token` ：获取身份验证令牌\n\n### 使用客户端\n\n```bash\n# Add a new error record\nmcp-client --action add --error-type ImportError --language python --error-message \"No module named 'requests'\" --solution-description \"Install requests\" --solution-explanation \"You need to install the requests package\"\n\n# Get an error by ID\nmcp-client --action get --id \n\n# Search for errors\nmcp-client --action search --error-type ImportError --language python\n\n# Find similar errors\nmcp-client --action similar --query \"ModuleNotFoundError: No module named 'pandas'\"\n```\n\n### 工作原理\n\n1. Tribal 使用 ChromaDB 存储错误记录和解决方案\n2. 当 Claude 遇到错误时，它会将错误详细信息发送给 Tribal\n3. Tribal 将错误向量化并搜索类似的错误\n4. 克劳德拿回相关解决方案建议\n5. 存储新的解决方案以供将来参考\n\n## 发展\n\n### 运行测试\n\n```bash\npytest\npytest tests/path_to_test.py::test_name # For specific tests\n```\n\n### Linting 和类型检查\n\n```bash\nruff check .\nmypy .\nblack .\n```\n\n### GitHub 工作流程\n\n该项目使用 GitHub Actions 进行持续集成和部署。工作流程会自动在推送到主代码和拉取请求时运行测试、代码检查和类型检查。\n\n#### 工作流程步骤\n\n1. **测试**：运行 linting、类型检查和单元测试\n\n * 使用 Python 3.12\n * 使用 uv 安装依赖项\n * 运行 ruff、black、mypy 和 pytest\n\n2. **构建并发布**：构建包并将其发布到 PyPI\n\n * 仅在推送到主分支时触发\n * 使用 Python 的构建系统\n * 使用 twine 发布到 PyPI\n\n#### 本地测试\n\n您可以使用提供的脚本在本地测试 GitHub 工作流程：\n\n```bash\n# Make the script executable\nchmod +x scripts/test-workflow.sh\n\n# Run the workflow locally\n./scripts/test-workflow.sh\n```\n\n此脚本在您的本地机器上模拟 GitHub 工作流程步骤：\n\n* 检查 Python 版本（建议 3.12）\n* 使用 uv 安装依赖项\n* 使用 ruff 进行除毛\n* 用黑色检查格式\n* 使用 mypy 运行类型检查\n* 使用 pytest 运行测试\n* 构建包\n\n注意：该脚本跳过本地测试的发布步骤。\n\n### 项目结构\n\n```\ntribal/\n├── src/\n│ ├── mcp_server_tribal/ # Core package\n│ │ ├── api/ # FastAPI endpoints\n│ │ ├── cli/ # Command-line interface\n│ │ ├── models/ # Pydantic models\n│ │ ├── services/ # Service layer\n│ │ │ ├── aws/ # AWS integrations\n│ │ │ └── chroma_storage.py # ChromaDB implementation\n│ │ └── utils/ # Utility functions\n│ └── examples/ # Example usage code\n├── tests/ # pytest test suite\n├── docker-compose.yml # Docker production setup\n├── pyproject.toml # Project configuration\n├── VERSIONING.md # Versioning strategy documentation\n├── CHANGELOG.md # Version history\n├── .bumpversion.cfg # Version bumping configuration\n└── README.md # Project documentation\n```\n\n## 版本控制\n\nTribal 遵循[语义版本控制](https://semver.org/)。有关以下内容的完整详细信息，请参阅[VERSIONING.md](VERSIONING.md) ：\n\n* 版本编号（MAJOR.MINOR.PATCH）\n* 数据库兼容性的架构版本控制\n* 分支命名约定\n* 发布和修补程序程序\n\n使用以下命令检查版本：\n\n```bash\n# Display version information\ntribal version\n```\n\n### 管理依赖关系\n\n```bash\n# Add a dependency\nuv pip add \n\n# Add a development dependency\nuv pip add \n\n# Update dependencies\nuv pip sync requirements.txt requirements-dev.txt\n```\n\n## 部署\n\n### Docker 部署\n\n```bash\n# Build and start containers\ndocker-compose up -d --build\n\n# View logs\ndocker-compose logs -f\n\n# Stop containers\ndocker-compose down\n\n# With custom environment variables\nAPI_PORT=8080 MCP_PORT=5000 REQUIRE_AUTH=true API_KEY=your-secret-key docker-start\n```\n\n### Claude 用于桌面集成\n\n#### 选项 1：让 Claude for Desktop 启动服务器\n\n1. 打开`~/Library/Application Support/Claude/claude_desktop_config.json`\n\n2. 添加 MCP 服务器配置（假设 Tribal 工具已安装）：\n\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"launchCommand\": \"tribal\"\n }\n ]\n }\n ```\n\n3. 重启 Claude 桌面版\n\n#### 选项 2：连接到正在运行的 Docker 容器\n\n1. 启动容器：\n\n ```bash\n cd /path/to/tribal\n docker-start\n ```\n\n2. 配置 Claude 桌面版：\n\n ```json\n {\n \"mcpServers\": [\n {\n \"name\": \"tribal\",\n \"url\": \"http://localhost:5000\"\n }\n ]\n }\n ```\n\n### Claude Code CLI 集成\n\n```bash\n# For Docker container\nclaude mcp add tribal http://localhost:5000\n\n# For directly launched server\nclaude mcp add tribal --launch \"tribal\"\n\n# Test the connection\nclaude mcp list\nclaude mcp test tribal\n```\n\n## 故障排除\n\n1. 验证部落安装： `which tribal`\n2. 检查配置： `claude mcp list`\n3. 测试服务器状态： `tribal status`\n4. 在 Claude 输出中查找错误消息\n5. 检查数据库目录是否存在并且具有适当的权限\n\n## 云部署\n\n该项目包括 AWS 服务的占位符实现：\n\n* `S3Storage` ：用于在 Amazon S3 中存储错误记录\n* `DynamoDBStorage` ：使用 DynamoDB 作为数据库\n\n## 执照\n\n[MIT 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