- CLAUDE.md for AI agents to understand the codebase - GITEA-GUIDE.md centralizes all Gitea operations (API, Registry, Auth) - DEVELOPMENT-WORKFLOW.md explains complete dev process - ROADMAP.md, NEXT-SESSION.md for planning - QUICK-REFERENCE.md, TROUBLESHOOTING.md for daily use - 40+ detailed docs in /docs folder - Backend as submodule from Gitea Everything documented for autonomous operation. Co-Authored-By: Claude Sonnet 4.5 (1M context) <noreply@anthropic.com>
453 lines
9.0 KiB
Markdown
453 lines
9.0 KiB
Markdown
# MCP Tools - Herramientas Disponibles para Agentes
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Esta documentación detalla todas las herramientas MCP que los agentes Claude Code pueden usar para interactuar con el sistema AiWorker.
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## get_next_task
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Obtiene la siguiente tarea disponible de la cola y la asigna al agente.
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**Input**:
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```json
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{
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"agentId": "uuid-of-agent",
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"capabilities": ["javascript", "react", "python"] // opcional
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}
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```
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**Output**:
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```json
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{
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"task": {
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"id": "task-uuid",
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"title": "Implement user authentication",
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"description": "Create a JWT-based authentication system...",
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"priority": "high",
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"project": {
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"id": "project-uuid",
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"name": "My App",
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"giteaRepoUrl": "http://gitea/owner/my-app",
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"dockerImage": "myapp:latest"
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}
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}
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}
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```
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**Ejemplo de uso**:
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```typescript
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// En Claude Code, el agente puede hacer:
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const task = await mcp.callTool('get_next_task', {
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agentId: process.env.AGENT_ID,
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capabilities: ['javascript', 'typescript', 'react']
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})
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```
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---
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## update_task_status
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Actualiza el estado de una tarea.
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**Input**:
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```json
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{
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"taskId": "task-uuid",
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"status": "in_progress" | "needs_input" | "ready_to_test" | "completed",
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"metadata": {
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"durationMinutes": 45,
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"linesChanged": 250
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}
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}
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```
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**Output**:
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```json
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{
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"success": true
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}
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```
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**Estados válidos**:
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- `in_progress`: Agente trabajando activamente
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- `needs_input`: Agente necesita información del usuario
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- `ready_to_test`: Tarea completada, lista para testing
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- `completed`: Tarea completamente finalizada
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---
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## ask_user_question
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Solicita información al usuario cuando el agente necesita clarificación.
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**Input**:
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```json
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{
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"taskId": "task-uuid",
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"question": "Which authentication library should I use: Passport.js or NextAuth?",
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"context": "The task requires implementing OAuth authentication. I found two popular options..."
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}
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```
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**Output**:
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```json
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{
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"success": true,
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"message": "Question sent to user",
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"questionId": "question-uuid"
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}
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```
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**Comportamiento**:
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1. Cambia el estado de la tarea a `needs_input`
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2. Notifica al frontend vía WebSocket
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3. Usuario responde desde el dashboard
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4. Agente puede hacer polling con `check_question_response`
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---
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## check_question_response
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Verifica si el usuario ha respondido una pregunta.
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**Input**:
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```json
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{
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"taskId": "task-uuid"
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}
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```
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**Output (sin respuesta)**:
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```json
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{
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"hasResponse": false,
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"message": "No response yet"
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}
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```
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**Output (con respuesta)**:
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```json
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{
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"hasResponse": true,
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"response": "Use NextAuth, it integrates better with our Next.js stack",
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"question": "Which authentication library should I use..."
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}
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```
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---
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## create_branch
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Crea una nueva rama en Gitea para la tarea.
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**Input**:
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```json
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{
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"taskId": "task-uuid",
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"branchName": "feature/user-auth" // opcional, se genera automático
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}
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```
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**Output**:
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```json
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{
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"success": true,
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"branchName": "task-abc123-implement-user-authentication",
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"repoUrl": "http://gitea/owner/my-app"
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}
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```
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**Comportamiento**:
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- Si no se especifica `branchName`, se genera como: `task-{shortId}-{title-slugified}`
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- Se crea desde la rama default del proyecto (main/develop)
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- Se actualiza el campo `branchName` en la tarea
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---
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## create_pull_request
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Crea un Pull Request en Gitea con los cambios de la tarea.
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**Input**:
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```json
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{
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"taskId": "task-uuid",
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"title": "Implement JWT-based authentication",
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"description": "## Changes\n- Added JWT middleware\n- Created auth routes\n- Added tests\n\n## Test Plan\n- [ ] Test login flow\n- [ ] Test token refresh"
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}
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```
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**Output**:
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```json
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{
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"success": true,
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"prUrl": "http://gitea/owner/my-app/pulls/42",
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"prNumber": 42
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}
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```
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**Comportamiento**:
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- Crea PR desde la rama de la tarea hacia la rama default
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- Actualiza campos `prNumber` y `prUrl` en la tarea
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- Emite evento WebSocket `task:pr_created`
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---
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## trigger_preview_deploy
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Despliega la tarea en un preview environment aislado en Kubernetes.
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**Input**:
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```json
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{
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"taskId": "task-uuid"
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}
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```
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**Output**:
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```json
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{
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"success": true,
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"previewUrl": "https://task-abc123.preview.aiworker.dev",
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"namespace": "preview-task-abc123"
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}
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```
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**Comportamiento**:
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1. Crea namespace en K8s: `preview-task-{shortId}`
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2. Deploya la aplicación con la imagen del proyecto
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3. Crea ingress con URL única
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4. Actualiza tarea a estado `ready_to_test`
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5. Guarda `previewUrl` y `previewNamespace` en la tarea
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---
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## get_task_details
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Obtiene detalles completos de una tarea incluyendo preguntas pendientes.
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**Input**:
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```json
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{
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"taskId": "task-uuid"
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}
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```
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**Output**:
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```json
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{
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"task": {
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"id": "task-uuid",
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"title": "Implement user authentication",
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"description": "...",
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"state": "needs_input",
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"branchName": "task-abc123-implement-user-authentication",
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"prUrl": "http://gitea/owner/my-app/pulls/42",
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"previewUrl": "https://task-abc123.preview.aiworker.dev",
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"questions": [
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{
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"id": "q-uuid",
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"question": "Which auth library?",
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"status": "pending",
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"askedAt": "2026-01-19T10:00:00Z"
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}
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],
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"project": {
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"name": "My App",
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"giteaRepoUrl": "..."
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}
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}
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}
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```
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---
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## log_activity
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Registra actividad del agente en los logs del sistema.
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**Input**:
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```json
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{
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"agentId": "agent-uuid",
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"level": "info" | "debug" | "warn" | "error",
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"message": "Starting task implementation",
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"metadata": {
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"taskId": "task-uuid",
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"operation": "code_generation",
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"filesModified": 5
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}
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}
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```
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**Output**:
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```json
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{
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"success": true
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}
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```
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**Niveles de log**:
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- `debug`: Información detallada de debugging
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- `info`: Eventos normales (default)
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- `warn`: Situaciones que requieren atención
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- `error`: Errores que impidieron completar una operación
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---
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## heartbeat
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Envía señal de vida para indicar que el agente está activo.
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**Input**:
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```json
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{
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"agentId": "agent-uuid",
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"status": "idle" | "busy" | "error"
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}
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```
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**Output**:
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```json
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{
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"success": true
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}
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```
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**Comportamiento**:
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- Actualiza `lastHeartbeat` timestamp
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- Actualiza `status` del agente
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- Si no se recibe heartbeat por 5 minutos, el agente se marca como `offline`
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---
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## Flujo Típico de una Tarea
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```mermaid
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sequenceDiagram
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Agent->>MCP: get_next_task()
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MCP-->>Agent: task details
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Agent->>MCP: create_branch()
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Agent->>Agent: Work on task
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Agent->>?MCP: ask_user_question() (si necesita)
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Agent->>Agent: Wait for response
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Agent->>MCP: check_question_response()
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Agent->>Agent: Continue working
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Agent->>Git: commit & push
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Agent->>MCP: create_pull_request()
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Agent->>MCP: trigger_preview_deploy()
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Agent->>MCP: update_task_status("ready_to_test")
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```
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## Ejemplo de Uso Completo
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```typescript
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// Dentro del agente Claude Code
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async function processTask() {
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// 1. Get task
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const taskResult = await mcp.callTool('get_next_task', {
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agentId: process.env.AGENT_ID
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})
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const task = JSON.parse(taskResult.content[0].text).task
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if (!task) {
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console.log('No tasks available')
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return
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}
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console.log(`Working on: ${task.title}`)
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// 2. Create branch
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const branchResult = await mcp.callTool('create_branch', {
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taskId: task.id
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})
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const { branchName } = JSON.parse(branchResult.content[0].text)
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// 3. Clone and checkout
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await exec(`git clone ${task.project.giteaRepoUrl} /workspace/task-${task.id}`)
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await exec(`cd /workspace/task-${task.id} && git checkout ${branchName}`)
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// 4. Do the work...
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// (Claude Code generates and commits code)
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// 5. Need clarification?
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if (needsClarification) {
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await mcp.callTool('ask_user_question', {
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taskId: task.id,
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question: 'Should I add error handling for network failures?',
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context: 'The API calls can fail...'
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})
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// Wait for response
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let response
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while (!response) {
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await sleep(5000)
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const checkResult = await mcp.callTool('check_question_response', {
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taskId: task.id
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})
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const check = JSON.parse(checkResult.content[0].text)
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if (check.hasResponse) {
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response = check.response
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}
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}
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}
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// 6. Create PR
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await mcp.callTool('create_pull_request', {
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taskId: task.id,
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title: task.title,
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description: `## Summary\nImplemented ${task.title}\n\n## Changes\n- Feature A\n- Feature B`
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})
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// 7. Deploy preview
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await mcp.callTool('trigger_preview_deploy', {
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taskId: task.id
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})
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// 8. Mark as done
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await mcp.callTool('update_task_status', {
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taskId: task.id,
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status: 'ready_to_test'
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})
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console.log('Task completed!')
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}
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```
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## Error Handling
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Todos los tools pueden retornar errores:
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```json
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{
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"content": [{
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"type": "text",
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"text": "Error: Task not found"
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}],
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"isError": true
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}
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```
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El agente debe manejar estos errores apropiadamente:
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```typescript
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const result = await mcp.callTool('update_task_status', { ... })
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if (result.isError) {
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console.error('Tool failed:', result.content[0].text)
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// Handle error
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}
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```
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## Rate Limiting
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Para evitar abuse, los tools tienen rate limits:
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- `get_next_task`: 1 por segundo
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- `ask_user_question`: 5 por minuto por tarea
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- `create_pr`: 1 por minuto
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- `trigger_preview_deploy`: 1 por minuto
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- Otros: 10 por segundo
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Si se excede el rate limit, el tool retorna error 429.
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