# SAFLA MCP Tools for Memory Manager Mode

## Memory Optimization Tools

### optimize_memory_usage
Optimize SAFLA memory usage and performance with configurable optimization levels.

**Usage:**
```javascript
use_mcp_tool({
  server_name: "safla",
  tool_name: "optimize_memory_usage",
  arguments: {
    optimization_level: "balanced",  // conservative, balanced, aggressive
    target_memory_mb: 4096          // Optional target memory usage
  }
})
```

**Parameters:**
- `optimization_level`: Optimization aggressiveness (conservative/balanced/aggressive)
- `target_memory_mb`: Target memory usage in megabytes (optional)

**Example Applications:**
```javascript
// Conservative optimization for production environments
await use_mcp_tool({
  server_name: "safla",
  tool_name: "optimize_memory_usage",
  arguments: {
    optimization_level: "conservative",
    target_memory_mb: 6144
  }
});

// Aggressive optimization for development/testing
await use_mcp_tool({
  server_name: "safla",
  tool_name: "optimize_memory_usage",
  arguments: {
    optimization_level: "aggressive",
    target_memory_mb: 2048
  }
});
```

### optimize_vector_operations
Optimize vector memory operations for better performance with configurable batch sizes and GPU acceleration.

**Usage:**
```javascript
use_mcp_tool({
  server_name: "safla",
  tool_name: "optimize_vector_operations",
  arguments: {
    batch_size: 100,    // Batch size for vector operations
    use_gpu: true       // Use GPU acceleration if available
  }
})
```

**Parameters:**
- `batch_size`: Batch size for vector operations (default: 100)
- `use_gpu`: Enable GPU acceleration if available (default: true)

**Example Applications:**
```javascript
// High-throughput vector processing
await use_mcp_tool({
  server_name: "safla",
  tool_name: "optimize_vector_operations",
  arguments: {
    batch_size: 500,
    use_gpu: true
  }
});

// Memory-constrained environments
await use_mcp_tool({
  server_name: "safla",
  tool_name: "optimize_vector_operations",
  arguments: {
    batch_size: 50,
    use_gpu: false
  }
});
```

## Memory Validation and Testing

### validate_memory_operations
Validate memory operations and data integrity with configurable test parameters.

**Usage:**
```javascript
use_mcp_tool({
  server_name: "safla",
  tool_name: "validate_memory_operations",
  arguments: {
    test_data_size: 10,           // Size of test data in MB
    include_stress_test: false    // Include stress testing
  }
})
```

**Parameters:**
- `test_data_size`: Size of test data in megabytes (default: 10)
- `include_stress_test`: Include stress testing (default: false)

**Example Applications:**
```javascript
// Standard memory validation
await use_mcp_tool({
  server_name: "safla",
  tool_name: "validate_memory_operations",
  arguments: {
    test_data_size: 50,
    include_stress_test: false
  }
});

// Comprehensive validation with stress testing
await use_mcp_tool({
  server_name: "safla",
  tool_name: "validate_memory_operations",
  arguments: {
    test_data_size: 200,
    include_stress_test: true
  }
});
```

## Performance Benchmarking

### benchmark_vector_operations
Benchmark vector memory operations performance with configurable parameters.

**Usage:**
```javascript
use_mcp_tool({
  server_name: "safla",
  tool_name: "benchmark_vector_operations",
  arguments: {
    vector_count: 1000,        // Number of vectors to benchmark
    vector_dimensions: 512,    // Vector dimensions
    operations: ["add", "search", "update"]  // Operations to benchmark
  }
})
```

**Parameters:**
- `vector_count`: Number of vectors to benchmark (default: 1000)
- `vector_dimensions`: Vector dimensions (default: 512)
- `operations`: Operations to benchmark (optional)

**Example Applications:**
```javascript
// Standard vector benchmarking
await use_mcp_tool({
  server_name: "safla",
  tool_name: "benchmark_vector_operations",
  arguments: {
    vector_count: 5000,
    vector_dimensions: 768,
    operations: ["add", "search", "update", "delete"]
  }
});

// High-dimensional vector benchmarking
await use_mcp_tool({
  server_name: "safla",
  tool_name: "benchmark_vector_operations",
  arguments: {
    vector_count: 1000,
    vector_dimensions: 1536,
    operations: ["search", "similarity"]
  }
});
```

### benchmark_memory_performance
Benchmark memory subsystem performance with various access patterns.

**Usage:**
```javascript
use_mcp_tool({
  server_name: "safla",
  tool_name: "benchmark_memory_performance",
  arguments: {
    test_duration: 60,                           // Test duration in seconds
    memory_patterns: ["sequential", "random"]   // Memory access patterns
  }
})
```

**Parameters:**
- `test_duration`: Test duration in seconds (default: 60)
- `memory_patterns`: Memory access patterns to test (optional)

**Example Applications:**
```javascript
// Comprehensive memory benchmarking
await use_mcp_tool({
  server_name: "safla",
  tool_name: "benchmark_memory_performance",
  arguments: {
    test_duration: 300,
    memory_patterns: ["sequential", "random", "mixed", "stride"]
  }
});

// Quick memory performance check
await use_mcp_tool({
  server_name: "safla",
  tool_name: "benchmark_memory_performance",
  arguments: {
    test_duration: 30,
    memory_patterns: ["sequential", "random"]
  }
});
```

## Performance Analysis

### analyze_performance_bottlenecks
Analyze and identify performance bottlenecks in memory operations.

**Usage:**
```javascript
use_mcp_tool({
  server_name: "safla",
  tool_name: "analyze_performance_bottlenecks",
  arguments: {
    duration_seconds: 60,           // Duration to monitor
    include_memory_profile: true    // Include memory profiling
  }
})
```

**Parameters:**
- `duration_seconds`: Duration to monitor in seconds (default: 60)
- `include_memory_profile`: Include memory profiling (default: true)

**Example Applications:**
```javascript
// Detailed bottleneck analysis
await use_mcp_tool({
  server_name: "safla",
  tool_name: "analyze_performance_bottlenecks",
  arguments: {
    duration_seconds: 300,
    include_memory_profile: true
  }
});

// Quick bottleneck check
await use_mcp_tool({
  server_name: "safla",
  tool_name: "analyze_performance_bottlenecks",
  arguments: {
    duration_seconds: 60,
    include_memory_profile: false
  }
});
```

## Agent Management for Memory Operations

### create_agent_session
Create specialized memory management agent sessions.

**Usage:**
```javascript
use_mcp_tool({
  server_name: "safla",
  tool_name: "create_agent_session",
  arguments: {
    agent_type: "memory",
    session_config: {
      focus: "vector_optimization",
      vector_dimensions: 512,
      cache_size: 1024,
      optimization_level: "balanced"
    },
    timeout_seconds: 3600
  }
})
```

**Memory Agent Configurations:**
```javascript
// Vector optimization agent
const vectorAgent = {
  agent_type: "memory",
  session_config: {
    focus: "vector_optimization",
    vector_dimensions: 768,
    batch_size: 100,
    use_gpu: true,
    cache_strategy: "lru"
  }
};

// Memory profiling agent
const profilingAgent = {
  agent_type: "memory",
  session_config: {
    focus: "memory_profiling",
    profiling_depth: "comprehensive",
    sampling_rate: 1000,
    include_stack_traces: true
  }
};

// Cache management agent
const cacheAgent = {
  agent_type: "memory",
  session_config: {
    focus: "cache_management",
    cache_size: 2048,
    eviction_policy: "lru",
    hit_rate_target: 0.9
  }
};
```

### interact_with_agent
Send memory-specific commands to agent sessions.

**Memory Agent Commands:**
```javascript
// Optimize vector storage
await use_mcp_tool({
  server_name: "safla",
  tool_name: "interact_with_agent",
  arguments: {
    session_id: "memory_001",
    command: "optimize_vector_storage",
    parameters: {
      vector_count: 10000,
      dimensions: 512,
      compression_level: "balanced"
    }
  }
});

// Analyze memory usage patterns
await use_mcp_tool({
  server_name: "safla",
  tool_name: "interact_with_agent",
  arguments: {
    session_id: "memory_001",
    command: "analyze_usage_patterns",
    parameters: {
      time_window: "24h",
      pattern_types: ["allocation", "access", "deallocation"]
    }
  }
});

// Optimize cache configuration
await use_mcp_tool({
  server_name: "safla",
  tool_name: "interact_with_agent",
  arguments: {
    session_id: "memory_001",
    command: "optimize_cache",
    parameters: {
      target_hit_rate: 0.95,
      max_memory: 4096,
      eviction_strategy: "adaptive"
    }
  }
});
```

## Memory-Specific Workflow Patterns

### Memory Optimization Workflow
```javascript
async function optimizeMemoryWorkflow() {
  // 1. Analyze current memory performance
  const bottlenecks = await use_mcp_tool({
    server_name: "safla",
    tool_name: "analyze_performance_bottlenecks",
    arguments: {
      duration_seconds: 120,
      include_memory_profile: true
    }
  });

  // 2. Create memory optimization agent
  const memoryAgent = await use_mcp_tool({
    server_name: "safla",
    tool_name: "create_agent_session",
    arguments: {
      agent_type: "memory",
      session_config: {
        focus: "optimization",
        analysis_data: bottlenecks
      }
    }
  });

  // 3. Apply targeted optimizations
  if (bottlenecks.vector_operations_slow) {
    await use_mcp_tool({
      server_name: "safla",
      tool_name: "optimize_vector_operations",
      arguments: {
        batch_size: 200,
        use_gpu: true
      }
    });
  }

  if (bottlenecks.memory_usage_high) {
    await use_mcp_tool({
      server_name: "safla",
      tool_name: "optimize_memory_usage",
      arguments: {
        optimization_level: "balanced",
        target_memory_mb: bottlenecks.recommended_memory
      }
    });
  }

  // 4. Validate optimizations
  const validation = await use_mcp_tool({
    server_name: "safla",
    tool_name: "validate_memory_operations",
    arguments: {
      test_data_size: 100,
      include_stress_test: true
    }
  });

  return { bottlenecks, optimizations: validation };
}
```

### Vector Performance Tuning
```javascript
async function tuneVectorPerformance() {
  // 1. Benchmark current vector performance
  const baseline = await use_mcp_tool({
    server_name: "safla",
    tool_name: "benchmark_vector_operations",
    arguments: {
      vector_count: 5000,
      vector_dimensions: 768,
      operations: ["add", "search", "update"]
    }
  });

  // 2. Create vector optimization agent
  const vectorAgent = await use_mcp_tool({
    server_name: "safla",
    tool_name: "create_agent_session",
    arguments: {
      agent_type: "memory",
      session_config: {
        focus: "vector_optimization",
        baseline_performance: baseline
      }
    }
  });

  // 3. Optimize vector operations
  await use_mcp_tool({
    server_name: "safla",
    tool_name: "optimize_vector_operations",
    arguments: {
      batch_size: baseline.optimal_batch_size || 150,
      use_gpu: true
    }
  });

  // 4. Benchmark optimized performance
  const optimized = await use_mcp_tool({
    server_name: "safla",
    tool_name: "benchmark_vector_operations",
    arguments: {
      vector_count: 5000,
      vector_dimensions: 768,
      operations: ["add", "search", "update"]
    }
  });

  return {
    baseline_performance: baseline,
    optimized_performance: optimized,
    improvement: calculateImprovement(baseline, optimized)
  };
}
```

### Memory Health Monitoring
```javascript
async function monitorMemoryHealth() {
  // 1. Continuous memory validation
  const validation = await use_mcp_tool({
    server_name: "safla",
    tool_name: "validate_memory_operations",
    arguments: {
      test_data_size: 50,
      include_stress_test: false
    }
  });

  // 2. Performance benchmarking
  const performance = await use_mcp_tool({
    server_name: "safla",
    tool_name: "benchmark_memory_performance",
    arguments: {
      test_duration: 60,
      memory_patterns: ["sequential", "random"]
    }
  });

  // 3. Bottleneck analysis
  const bottlenecks = await use_mcp_tool({
    server_name: "safla",
    tool_name: "analyze_performance_bottlenecks",
    arguments: {
      duration_seconds: 60,
      include_memory_profile: true
    }
  });

  // 4. Generate health report
  return {
    validation_status: validation.status,
    performance_metrics: performance.metrics,
    identified_bottlenecks: bottlenecks.bottlenecks,
    health_score: calculateHealthScore(validation, performance, bottlenecks)
  };
}
```

## Error Handling and Recovery

### Memory Error Recovery
```javascript
async function handleMemoryError(error) {
  try {
    // 1. Validate memory operations
    const validation = await use_mcp_tool({
      server_name: "safla",
      tool_name: "validate_memory_operations",
      arguments: {
        test_data_size: 10,
        include_stress_test: false
      }
    });

    if (!validation.success) {
      // 2. Apply conservative memory optimization
      await use_mcp_tool({
        server_name: "safla",
        tool_name: "optimize_memory_usage",
        arguments: {
          optimization_level: "conservative"
        }
      });

      // 3. Re-validate after optimization
      const revalidation = await use_mcp_tool({
        server_name: "safla",
        tool_name: "validate_memory_operations",
        arguments: {
          test_data_size: 5,
          include_stress_test: false
        }
      });

      return revalidation;
    }

    return validation;
  } catch (recoveryError) {
    console.error("Memory recovery failed:", recoveryError);
    throw new Error("Critical memory error - manual intervention required");
  }
}