aserrador
b520d47ab3
- Add Dockerfile using uv for dependency management - Add docker-compose.yaml for container orchestration - Add .dockerignore to optimize builds - Update taskipy start task with http transport and port 3001 - Update README.md and AGENTS.md with Docker documentation
161 lines
3.8 KiB
Markdown
161 lines
3.8 KiB
Markdown
# TrytonMCP Agent Specification
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## Desarrollo
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### Configuración inicial
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```bash
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# Instalar dependencias con uv
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uv sync
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# Copiar configuración de ejemplo
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cp .env.example .env
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# Instalar dependencias de desarrollo y test
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uv pip install -e ".[test]"
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```
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### Comandos frecuentes
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```bash
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# Ejecutar servidor MCP (stdio)
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uv run fastmcp run src/tryton_mcp/server.py
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# Ejecutar tests
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python -m pytest tests/ -v
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# Verificar código
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ruff check src/ tests/
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ruff format src/ tests/
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```
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### Docker
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```bash
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# Construir imagen
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docker compose build
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# Iniciar contenedor
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docker compose up -d
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# Ver logs
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docker compose logs -f
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# Detener
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docker compose down
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```
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### Agregar nueva herramienta
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```python
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from tryton_mcp.services.base import TrytonService
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class YourService(TrytonService):
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name = "your.model.method"
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def execute(self, params: dict) -> List[dict]:
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# Implementar lógica
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pass
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```
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## Overview
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TrytonMCP es un servidor MCP (Model Context Protocol) que permite a los LLMs interactuar con Tryton ERP a través de llamadas RPC. Envuelve la librería `sabatron-tryton_rpc_client` y expone los modelos de Tryton como herramientas invocables.
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## Project Structure
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```
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TrytonMCP/
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├── src/
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│ └── tryton_mcp/
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│ ├── __init__.py
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│ ├── config.py # Settings singleton with TrytonSettings
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│ ├── server.py # Main MCP server with tool definitions
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│ └── services/
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│ ├── base.py # TrytonService base class
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│ ├── party.py # Customer operations
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│ ├── product.py # Products/Services
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│ ├── schedule.py # Appointments
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│ └── service_center.py # Service centers
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├── tests/ # Test suite
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│ ├── conftest.py
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│ ├── test_customer.py
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│ └── test_server.py
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├── test_rpc.py # Standalone RPC test script
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├── Dockerfile # Docker container definition
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├── docker-compose.yaml # Docker Compose orchestration
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├── .dockerignore # Docker build exclusions
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├── pyproject.toml # Project dependencies
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└── .env.example # Environment variables template
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```
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## Architecture
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### Dependencies
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- **fastmcp[tasks]>=3.1.0** - MCP server framework
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- **sabatron-tryton-rpc-client>=7.4.0** - Tryton RPC client
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### Core Components
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1. **Settings** (`config.py`) - Singleton pattern for configuration management
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- Uses environment variables with defaults
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- Provides `to_dict()` and `get_client()` methods
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- Validates required fields in `__post_init__`
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2. **Tools** (`server.py`) - Functions decorated with `@mcp.tool()`:
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- `create_schedule` - Creates appointments in Naliia module
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- `find_service_centers` - Searches service centers
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- `find_products_and_services` - Searches salable products
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## Adding New Tools
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To add a new Tryton model as an MCP tool:
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```python
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@mcp.tool()
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def your_tool_name(param1: int, param2: str) -> List[dict]:
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client = settings.get_client()
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client.connect()
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name = "model.your.model.method"
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args = [params, ...]
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response = client.call(name, args)
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return response
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```
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## Running the Server
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```bash
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# Run MCP server (stdio mode)
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uv run fastmcp run src/tryton_mcp/server.py
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```
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## Configuration
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Credentials are loaded from environment variables (with sensible defaults):
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```bash
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export TRYTON_HOSTNAME=dev.naliia.co
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export TRYTON_DATABASE=capacitacion
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export TRYTON_USERNAME=admin
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export TRYTON_PASSWORD=admin
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export TRYTON_PORT=8000
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```
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Or copy `.env.example` to `.env` and adjust values:
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```bash
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cp .env.example .env
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```
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Note: `.env` is gitignored to protect credentials.
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## Testing RPC Calls
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Use `test_rpc.py` to test Tryton RPC calls independently:
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```bash
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python test_rpc.py
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```
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