#!/usr/bin/env python3
"""
MCP Integrations - Interfaces to other MCP servers
Provides unified interface to enhanced-memory, agent-runtime, and AGI orchestrator
"""
import logging
import httpx
import json
from typing import Dict, List, Optional, Any
logger = logging.getLogger("voice-agi.integrations")
class EnhancedMemoryClient:
"""Client for enhanced-memory MCP server"""
def __init__(self, base_url: str = "http://localhost:3000"):
"""
Initialize enhanced-memory client
Args:
base_url: Base URL for MCP server (adjust as needed)
"""
self.base_url = base_url
self.client = httpx.AsyncClient(timeout=30.0)
logger.info(f"Enhanced memory client initialized: {base_url}")
async def store_entity(self, entity: Dict[str, Any]) -> Dict[str, Any]:
"""
Store entity in enhanced memory
Args:
entity: Entity data to store
Returns:
Storage result
"""
try:
# TODO: Actual MCP call when integrated
# For now, just log
logger.info(f"Would store entity: {entity.get('type', 'unknown')}")
return {
'success': True,
'entity_id': f"entity_{hash(json.dumps(entity))}",
'type': entity.get('type')
}
except Exception as e:
logger.error(f"Error storing entity: {e}")
return {'success': False, 'error': str(e)}
async def search(
self,
query: str,
entity_type: Optional[str] = None,
limit: int = 10
) -> List[Dict[str, Any]]:
"""
Search enhanced memory
Args:
query: Search query
entity_type: Optional filter by entity type
limit: Maximum results
Returns:
List of matching entities
"""
try:
# TODO: Actual MCP call when integrated
logger.info(f"Would search memory: {query}")
# Simulate results
return [
{
'id': 'mem_1',
'type': entity_type or 'voice_conversation_turn',
'content': {'text': f"Result for: {query}"},
'relevance': 0.85
}
]
except Exception as e:
logger.error(f"Error searching memory: {e}")
return []
async def get_entity(self, entity_id: str) -> Optional[Dict[str, Any]]:
"""Get entity by ID"""
try:
# TODO: Actual MCP call
logger.info(f"Would get entity: {entity_id}")
return None
except Exception as e:
logger.error(f"Error getting entity: {e}")
return None
async def close(self):
"""Close HTTP client"""
await self.client.aclose()
class AgentRuntimeClient:
"""Client for agent-runtime MCP server"""
def __init__(self, base_url: str = "http://localhost:3001"):
"""
Initialize agent-runtime client
Args:
base_url: Base URL for MCP server
"""
self.base_url = base_url
self.client = httpx.AsyncClient(timeout=30.0)
logger.info(f"Agent runtime client initialized: {base_url}")
async def create_goal(
self,
name: str,
description: str,
metadata: Optional[Dict] = None
) -> Dict[str, Any]:
"""
Create new goal
Args:
name: Goal name
description: Goal description
metadata: Optional metadata
Returns:
Created goal
"""
try:
# TODO: Actual MCP call
logger.info(f"Would create goal: {name}")
return {
'goal_id': f"goal_{hash(name)}",
'name': name,
'description': description,
'status': 'active',
'created': True
}
except Exception as e:
logger.error(f"Error creating goal: {e}")
return {'error': str(e)}
async def decompose_goal(
self,
goal_id: str,
strategy: str = "sequential"
) -> Dict[str, Any]:
"""
Decompose goal into tasks
Args:
goal_id: Goal ID
strategy: Decomposition strategy
Returns:
Decomposed tasks
"""
try:
# TODO: Actual MCP call
logger.info(f"Would decompose goal: {goal_id}")
return {
'goal_id': goal_id,
'tasks': [
{'task_id': 'task_1', 'title': 'Step 1', 'status': 'pending'},
{'task_id': 'task_2', 'title': 'Step 2', 'status': 'pending'}
],
'count': 2
}
except Exception as e:
logger.error(f"Error decomposing goal: {e}")
return {'error': str(e)}
async def create_task(
self,
title: str,
description: Optional[str] = None,
goal_id: Optional[str] = None,
priority: int = 5
) -> Dict[str, Any]:
"""
Create new task
Args:
title: Task title
description: Task description
goal_id: Optional associated goal
priority: Task priority (1-10)
Returns:
Created task
"""
try:
# TODO: Actual MCP call
logger.info(f"Would create task: {title}")
return {
'task_id': f"task_{hash(title)}",
'title': title,
'description': description,
'status': 'pending',
'priority': priority,
'created': True
}
except Exception as e:
logger.error(f"Error creating task: {e}")
return {'error': str(e)}
async def list_tasks(
self,
status: Optional[str] = None,
limit: int = 50
) -> List[Dict[str, Any]]:
"""
List tasks
Args:
status: Optional filter by status
limit: Maximum results
Returns:
List of tasks
"""
try:
# TODO: Actual MCP call
logger.info(f"Would list tasks (status={status})")
return [
{'task_id': 'task_1', 'title': 'Example task 1', 'status': 'pending'},
{'task_id': 'task_2', 'title': 'Example task 2', 'status': 'in_progress'}
]
except Exception as e:
logger.error(f"Error listing tasks: {e}")
return []
async def get_task(self, task_id: str) -> Optional[Dict[str, Any]]:
"""Get task by ID"""
try:
# TODO: Actual MCP call
logger.info(f"Would get task: {task_id}")
return None
except Exception as e:
logger.error(f"Error getting task: {e}")
return None
async def update_task_status(
self,
task_id: str,
status: str
) -> Dict[str, Any]:
"""Update task status"""
try:
# TODO: Actual MCP call
logger.info(f"Would update task {task_id} to {status}")
return {
'task_id': task_id,
'status': status,
'updated': True
}
except Exception as e:
logger.error(f"Error updating task: {e}")
return {'error': str(e)}
async def close(self):
"""Close HTTP client"""
await self.client.aclose()
class AGIOrchestratorClient:
"""Client for AGI orchestrator"""
def __init__(self, base_url: str = "http://localhost:8000"):
"""
Initialize AGI orchestrator client
Args:
base_url: Base URL for orchestrator
"""
self.base_url = base_url
self.client = httpx.AsyncClient(timeout=60.0)
logger.info(f"AGI orchestrator client initialized: {base_url}")
async def trigger_consolidation(self) -> Dict[str, Any]:
"""Trigger memory consolidation cycle"""
try:
# TODO: Actual API call
logger.info("Would trigger consolidation")
return {
'status': 'started',
'consolidation_id': 'cons_123',
'estimated_time': 30
}
except Exception as e:
logger.error(f"Error triggering consolidation: {e}")
return {'error': str(e)}
async def start_research(self, topic: str) -> Dict[str, Any]:
"""Start autonomous research"""
try:
# TODO: Actual API call
logger.info(f"Would start research: {topic}")
return {
'research_id': f"research_{hash(topic)}",
'topic': topic,
'status': 'started'
}
except Exception as e:
logger.error(f"Error starting research: {e}")
return {'error': str(e)}
async def start_improvement_cycle(self, target_metric: str) -> Dict[str, Any]:
"""Start self-improvement cycle"""
try:
# TODO: Actual API call
logger.info(f"Would start improvement cycle: {target_metric}")
return {
'cycle_id': f"cycle_{hash(target_metric)}",
'target_metric': target_metric,
'status': 'started'
}
except Exception as e:
logger.error(f"Error starting improvement cycle: {e}")
return {'error': str(e)}
async def get_system_status(self) -> Dict[str, Any]:
"""Get AGI system status"""
try:
# TODO: Actual API call
logger.info("Would get system status")
return {
'status': 'operational',
'active_agents': 12,
'memory_usage': '2.3 GB',
'uptime_hours': 48
}
except Exception as e:
logger.error(f"Error getting system status: {e}")
return {'error': str(e)}
async def close(self):
"""Close HTTP client"""
await self.client.aclose()
# Global clients (initialized lazily)
_memory_client: Optional[EnhancedMemoryClient] = None
_runtime_client: Optional[AgentRuntimeClient] = None
_orchestrator_client: Optional[AGIOrchestratorClient] = None
def get_memory_client() -> EnhancedMemoryClient:
"""Get or create enhanced-memory client"""
global _memory_client
if _memory_client is None:
_memory_client = EnhancedMemoryClient()
return _memory_client
def get_runtime_client() -> AgentRuntimeClient:
"""Get or create agent-runtime client"""
global _runtime_client
if _runtime_client is None:
_runtime_client = AgentRuntimeClient()
return _runtime_client
def get_orchestrator_client() -> AGIOrchestratorClient:
"""Get or create AGI orchestrator client"""
global _orchestrator_client
if _orchestrator_client is None:
_orchestrator_client = AGIOrchestratorClient()
return _orchestrator_client
