Tools (MCP) Architecture

class MCPProtocolHandler:
    def __init__(self):
        self.protocol_version = "2.0"
        self.supported_transports = ["http", "websocket", "grpc"]
        self.message_handlers = self.setup_handlers()
        
    def setup_handlers(self) -> Dict[str, MessageHandler]:
        return {
            "tool_discovery": ToolDiscoveryHandler(),
            "tool_invocation": ToolInvocationHandler(),
            "stream_processing": StreamProcessingHandler(),
            "error_handling": ErrorHandlingHandler(),
            "authentication": AuthenticationHandler()
        }
        
    async def handle_message(self, message: MCPMessage) -> MCPResponse:
        handler = self.message_handlers.get(message.type)
        if not handler:
            raise UnsupportedMessageTypeError(message.type)
            
        # Validate message
        validation_result = await self.validate_message(message)
        if not validation_result.is_valid:
            return MCPErrorResponse(validation_result.errors)
            
        # Process message
        try:
            response = await handler.handle(message)
            return response
        except Exception as e:
            return MCPErrorResponse([str(e)])

mcp_message_types:
  discovery:
    - server_capabilities
    - tool_list_request
    - tool_schema_request
    - health_check
    
  invocation:
    - tool_call_request
    - stream_start
    - stream_data
    - stream_end
    
  control:
    - connection_init
    - authentication
    - permission_check
    - rate_limit_check
    
  monitoring:
    - performance_metrics
    - error_reports
    - usage_statistics
    - health_status

class TransportManager:
    def __init__(self):
        self.transports = {
            "http": HTTPTransport(),
            "websocket": WebSocketTransport(),
            "grpc": GRPCTransport()
        }
        
    async def connect(self, server_url: str, transport_type: str) -> Connection:
        transport = self.transports.get(transport_type)
        if not transport:
            raise UnsupportedTransportError(transport_type)
            
        connection = await transport.connect(server_url)
        
        # Setup connection monitoring
        self.setup_connection_monitoring(connection)
        
        return connection
        
    def setup_connection_monitoring(self, connection: Connection):
        connection.add_monitor(HeartbeatMonitor())
        connection.add_monitor(PerformanceMonitor())
        connection.add_monitor(ErrorMonitor())

class ServerDiscovery:
    def __init__(self):
        self.discovery_methods = [
            DNSDiscovery(),
            ConsulDiscovery(),
            KubernetesDiscovery(),
            StaticConfigDiscovery()
        ]
        
    async def discover_servers(self) -> List[MCPServer]:
        discovered_servers = []
        
        for method in self.discovery_methods:
            try:
                servers = await method.discover()
                discovered_servers.extend(servers)
            except DiscoveryError as e:
                self.log_discovery_error(method, e)
                
        # Deduplicate and validate
        unique_servers = self.deduplicate_servers(discovered_servers)
        validated_servers = await self.validate_servers(unique_servers)
        
        return validated_servers
        
    async def validate_servers(self, servers: List[MCPServer]) -> List[MCPServer]:
        validated = []
        
        for server in servers:
            if await self.health_check(server):
                capabilities = await self.get_capabilities(server)
                server.capabilities = capabilities
                validated.append(server)
                
        return validated

service_registry:
  storage_backend: "etcd"
  registration_ttl: 300  # 5 minutes
  health_check_interval: 30  # seconds
  
  server_metadata:
    - server_id
    - server_url
    - protocol_version
    - supported_tools
    - capabilities
    - health_status
    - last_seen
    
  discovery_sources:
    - dns_srv_records
    - consul_services
    - kubernetes_endpoints
    - static_configuration

class LoadBalancer:
    def __init__(self):
        self.strategies = {
            "round_robin": RoundRobinStrategy(),
            "least_connections": LeastConnectionsStrategy(),
            "weighted": WeightedStrategy(),
            "health_aware": HealthAwareStrategy()
        }
        
    def select_server(self, servers: List[MCPServer], strategy: str = "health_aware") -> MCPServer:
        strategy_impl = self.strategies.get(strategy, self.strategies["round_robin"])
        
        # Filter healthy servers
        healthy_servers = [s for s in servers if s.health_status == "healthy"]
        
        if not healthy_servers:
            raise NoHealthyServersError()
            
        return strategy_impl.select(healthy_servers)

class ToolCatalog:
    def __init__(self):
        self.tools = {}
        self.categories = self.initialize_categories()
        
    def register_tool(self, tool: Tool) -> ToolRegistration:
        # Validate tool specification
        validation_result = self.validate_tool(tool)
        if not validation_result.is_valid:
            raise ToolValidationError(validation_result.errors)
            
        # Register tool
        tool_id = self.generate_tool_id(tool)
        registration = ToolRegistration(
            tool_id=tool_id,
            tool=tool,
            registration_time=datetime.utcnow(),
            version=tool.version,
            dependencies=self.resolve_dependencies(tool)
        )
        
        self.tools[tool_id] = registration
        self.update_categories(tool)
        
        return registration
        
    def search_tools(self, query: ToolQuery) -> List[Tool]:
        results = []
        
        for tool_id, registration in self.tools.items():
            tool = registration.tool
            
            # Match by capability
            if query.capability and query.capability in tool.capabilities:
                results.append(tool)
                continue
                
            # Match by category
            if query.category and tool.category == query.category:
                results.append(tool)
                continue
                
            # Text search in name/description
            if query.text and self.text_matches(tool, query.text):
                results.append(tool)
                
        return self.rank_results(results, query)

tool_schema:
  metadata:
    - tool_id: "unique_identifier"
    - name: "human_readable_name"
    - description: "detailed_description"
    - version: "semantic_version"
    - category: "tool_category"
    - provider: "provider_organization"
    
  capabilities:
    - supported_operations: ["read", "write", "execute"]
    - data_types: ["json", "binary", "stream"]
    - authentication_methods: ["api_key", "oauth", "mutual_tls"]
    - rate_limits: {"requests_per_minute": 1000}
    
  interface:
    - input_schema: "json_schema"
    - output_schema: "json_schema"
    - error_schema: "json_schema"
    - examples: ["usage_examples"]
    
  requirements:
    - permissions: ["required_permissions"]
    - resources: {"cpu": "100m", "memory": "256Mi"}
    - dependencies: ["dependency_list"]
    - environment: {"required_env_vars": []}

class VersionManager:
    def __init__(self):
        self.version_store = VersionStore()
        self.compatibility_matrix = CompatibilityMatrix()
        
    def register_version(self, tool_id: str, version: str, tool_spec: ToolSpec) -> VersionRegistration:
        # Check version format
        if not self.is_valid_version(version):
            raise InvalidVersionError(version)
            
        # Check compatibility
        compatibility = self.check_compatibility(tool_id, version, tool_spec)
        
        registration = VersionRegistration(
            tool_id=tool_id,
            version=version,
            tool_spec=tool_spec,
            compatibility=compatibility,
            registration_time=datetime.utcnow()
        )
        
        self.version_store.store(registration)
        return registration
        
    def resolve_version(self, tool_id: str, version_constraint: str) -> str:
        available_versions = self.version_store.get_versions(tool_id)
        compatible_versions = [
            v for v in available_versions 
            if self.satisfies_constraint(v, version_constraint)
        ]
        
        if not compatible_versions:
            raise NoCompatibleVersionError(tool_id, version_constraint)
            
        # Return latest compatible version
        return max(compatible_versions, key=lambda v: self.parse_version(v))

class SandboxedExecutor:
    def __init__(self):
        self.sandbox_config = self.load_sandbox_config()
        self.resource_limits = self.load_resource_limits()
        
    async def execute_tool(self, tool_call: ToolCall, context: ExecutionContext) -> ToolResult:
        # Create isolated sandbox
        sandbox = await self.create_sandbox(tool_call.tool_id)
        
        try:
            # Apply resource limits
            await sandbox.apply_limits(self.resource_limits)
            
            # Load tool
            tool = await self.load_tool(tool_call.tool_id, sandbox)
            
            # Execute with timeout
            result = await asyncio.wait_for(
                tool.execute(tool_call.parameters, context),
                timeout=tool_call.timeout or 300
            )
            
            # Validate result
            validated_result = await self.validate_result(result, tool.output_schema)
            
            return validated_result
            
        except Exception as e:
            await self.handle_execution_error(e, tool_call, sandbox)
            raise
        finally:
            await self.cleanup_sandbox(sandbox)

resource_management:
  limits:
    cpu:
      default: "500m"
      maximum: "2000m"
      burst_allowed: true
      
    memory:
      default: "512Mi"
      maximum: "2Gi"
      oom_handling: "graceful_termination"
      
    network:
      bandwidth: "100Mbps"
      connections: 100
      timeout: "30s"
      
    storage:
      temp_space: "1Gi"
      persistent: "10Gi"
      iops: 1000
      
  monitoring:
    metrics_collection: true
    resource_alerts: true
    usage_optimization: true
    automatic_scaling: false

class ExecutionErrorHandler:
    def __init__(self):
        self.error_strategies = {
            TimeoutError: self.handle_timeout,
            ResourceLimitError: self.handle_resource_limit,
            AuthenticationError: self.handle_auth_error,
            NetworkError: self.handle_network_error,
            ToolError: self.handle_tool_error
        }
        
    async def handle_error(self, error: Exception, context: ExecutionContext) -> ErrorResponse:
        error_type = type(error)
        handler = self.error_strategies.get(error_type, self.handle_generic_error)
        
        # Log error
        await self.log_error(error, context)
        
        # Apply recovery strategy
        recovery_action = await handler(error, context)
        
        return ErrorResponse(
            error_type=error_type.__name__,
            error_message=str(error),
            recovery_action=recovery_action,
            retry_possible=self.is_retryable(error),
            context=context
        )
        
    async def handle_timeout(self, error: TimeoutError, context: ExecutionContext) -> RecoveryAction:
        # Check if timeout is due to resource constraints
        if context.resource_usage.cpu > 0.9:
            return RecoveryAction.INCREASE_RESOURCES
        elif context.resource_usage.network_latency > 10:
            return RecoveryAction.RETRY_WITH_BACKOFF
        else:
            return RecoveryAction.INCREASE_TIMEOUT

class PermissionManager:
    def __init__(self):
        self.rbac = RoleBasedAccessControl()
        self.abac = AttributeBasedAccessControl()
        
    async def check_permission(self, agent_id: str, tool_id: str, operation: str, context: dict) -> PermissionResult:
        # Role-based check
        rbac_result = await self.rbac.check_permission(agent_id, tool_id, operation)
        
        # Attribute-based check
        abac_result = await self.abac.evaluate_policy(
            subject={"agent_id": agent_id},
            resource={"tool_id": tool_id, "operation": operation},
            environment=context
        )
        
        # Combine results
        final_result = rbac_result and abac_result
        
        return PermissionResult(
            allowed=final_result,
            rbac_result=rbac_result,
            abac_result=abac_result,
            reasons=self.get_decision_reasons(rbac_result, abac_result)
        )

access_policies:
  role_policies:
    discovery_agent:
      allowed_tools: ["database_read", "api_read", "file_read"]
      denied_tools: ["system_admin", "data_delete"]
      conditions:
        - time_of_day: "business_hours"
        - data_classification: "public_or_internal"
        
    operator_agent:
      allowed_tools: ["database_write", "api_write", "process_execute"]
      denied_tools: ["system_config", "user_management"]
      conditions:
        - approval_required: true
        - audit_logging: true
        
  attribute_policies:
    data_access:
      condition: "data.classification == 'public' OR (data.classification == 'internal' AND agent.clearance >= 'internal')"
      
    financial_operations:
      condition: "operation.amount < agent.spending_limit OR approval.required == true"
      
    system_modifications:
      condition: "agent.role == 'admin' AND time.hour >= 9 AND time.hour <= 17"

class AuditLogger:
    def __init__(self):
        self.storage = AuditStorage()
        self.compliance_checker = ComplianceChecker()
        
    async def log_tool_execution(self, execution: ToolExecution) -> AuditRecord:
        audit_record = AuditRecord(
            record_id=self.generate_record_id(),
            timestamp=datetime.utcnow(),
            agent_id=execution.agent_id,
            tool_id=execution.tool_id,
            operation=execution.operation,
            parameters=self.sanitize_parameters(execution.parameters),
            result_summary=self.summarize_result(execution.result),
            execution_time=execution.duration,
            resource_usage=execution.resource_usage,
            access_level=execution.access_level,
            compliance_tags=self.generate_compliance_tags(execution)
        )
        
        # Store audit record
        await self.storage.store(audit_record)
        
        # Check compliance
        compliance_result = await self.compliance_checker.check(audit_record)
        if not compliance_result.compliant:
            await self.handle_compliance_violation(audit_record, compliance_result)
            
        return audit_record

compliance_requirements:
  gdpr:
    data_processing_logging: required
    consent_tracking: required
    data_minimization: enforced
    right_to_erasure: supported
    
  sox:
    financial_data_access: logged
    segregation_of_duties: enforced
    change_management: required
    audit_trail_integrity: protected
    
  hipaa:
    phi_access_logging: required
    minimum_necessary: enforced
    access_controls: strict
    breach_notification: automated
    
  iso27001:
    access_controls: implemented
    incident_management: automated
    risk_assessment: continuous
    security_monitoring: comprehensive

class RateLimiter:
    def __init__(self):
        self.limiters = {
            "token_bucket": TokenBucketLimiter(),
            "sliding_window": SlidingWindowLimiter(),
            "fixed_window": FixedWindowLimiter(),
            "adaptive": AdaptiveLimiter()
        }
        
    async def check_rate_limit(self, agent_id: str, tool_id: str, operation: str) -> RateLimitResult:
        # Get rate limit configuration
        config = await self.get_rate_limit_config(agent_id, tool_id, operation)
        
        # Apply appropriate limiter
        limiter = self.limiters[config.algorithm]
        
        result = await limiter.check_limit(
            key=f"{agent_id}:{tool_id}:{operation}",
            limit=config.limit,
            window=config.window,
            current_time=datetime.utcnow()
        )
        
        if not result.allowed:
            await self.log_rate_limit_exceeded(agent_id, tool_id, operation, result)
            
        return result

quota_configuration:
  per_agent_quotas:
    daily_operations: 10000
    hourly_operations: 1000
    concurrent_operations: 50
    data_transfer_gb: 100
    
  per_tool_quotas:
    database_queries: 5000
    api_calls: 2000
    file_operations: 1000
    compute_minutes: 120
    
  dynamic_quotas:
    priority_scaling: true
    burst_allowance: 150%
    time_based_scaling: true
    performance_based_scaling: true
    
  quota_enforcement:
    soft_limits: "warning_notification"
    hard_limits: "operation_blocking"
    quota_reset: "daily_at_midnight"
    emergency_override: "admin_approval_required"

class ConnectionPoolManager:
    def __init__(self):
        self.pools = {}
        self.pool_config = self.load_pool_config()
        
    async def get_connection(self, server_url: str, tool_id: str) -> Connection:
        pool_key = f"{server_url}:{tool_id}"
        
        if pool_key not in self.pools:
            self.pools[pool_key] = await self.create_pool(server_url, tool_id)
            
        pool = self.pools[pool_key]
        connection = await pool.acquire()
        
        # Validate connection health
        if not await self.validate_connection(connection):
            await pool.release(connection, discard=True)
            connection = await pool.acquire()
            
        return connection
        
    async def create_pool(self, server_url: str, tool_id: str) -> ConnectionPool:
        config = self.pool_config.get(tool_id, self.pool_config["default"])
        
        pool = ConnectionPool(
            server_url=server_url,
            min_connections=config.min_connections,
            max_connections=config.max_connections,
            connection_timeout=config.connection_timeout,
            idle_timeout=config.idle_timeout,
            retry_attempts=config.retry_attempts
        )
        
        await pool.initialize()
        return pool

class CacheManager:
    def __init__(self):
        self.l1_cache = InMemoryCache(max_size=1000, ttl=300)
        self.l2_cache = RedisCache(ttl=3600)
        self.l3_cache = DistributedCache(ttl=86400)
        self.l4_cache = PersistentCache(ttl=604800)
        
    async def get(self, key: str) -> Optional[Any]:
        # Try L1 cache first
        result = await self.l1_cache.get(key)
        if result is not None:
            return result
            
        # Try L2 cache
        result = await self.l2_cache.get(key)
        if result is not None:
            await self.l1_cache.set(key, result)
            return result
            
        # Try L3 cache
        result = await self.l3_cache.get(key)
        if result is not None:
            await self.l2_cache.set(key, result)
            await self.l1_cache.set(key, result)
            return result
            
        # Try L4 cache
        result = await self.l4_cache.get(key)
        if result is not None:
            await self.l3_cache.set(key, result)
            await self.l2_cache.set(key, result)
            await self.l1_cache.set(key, result)
            return result
            
        return None
        
    async def set(self, key: str, value: Any, ttl: Optional[int] = None):
        # Store in all cache levels
        await self.l1_cache.set(key, value, ttl)
        await self.l2_cache.set(key, value, ttl)
        await self.l3_cache.set(key, value, ttl)
        await self.l4_cache.set(key, value, ttl)

performance_metrics:
  latency_metrics:
    - tool_discovery_time
    - connection_establishment_time
    - tool_execution_time
    - result_processing_time
    - end_to_end_latency
    
  throughput_metrics:
    - operations_per_second
    - concurrent_operations
    - data_transfer_rate
    - cache_hit_rate
    - connection_pool_utilization
    
  resource_metrics:
    - cpu_utilization
    - memory_consumption
    - network_bandwidth_usage
    - storage_io_operations
    - sandbox_resource_usage
    
  quality_metrics:
    - operation_success_rate
    - error_rate_by_type
    - retry_rate
    - timeout_rate
    - data_quality_score

database_tools:
  relational:
    - postgresql_connector
    - mysql_connector
    - oracle_connector
    - sql_server_connector
    
  nosql:
    - mongodb_connector
    - cassandra_connector
    - redis_connector
    - dynamodb_connector
    
  analytics:
    - clickhouse_connector
    - bigquery_connector
    - snowflake_connector
    - databricks_connector
    
  vector:
    - pinecone_connector
    - weaviate_connector
    - qdrant_connector
    - chroma_connector

api_tools:
  protocols:
    - rest_client
    - graphql_client
    - grpc_client
    - websocket_client
    
  authentication:
    - oauth2_authenticator
    - api_key_manager
    - jwt_handler
    - mutual_tls_client
    
  specialized:
    - webhook_manager
    - rate_limited_client
    - bulk_operation_client
    - streaming_client

file_tools:
  operations:
    - file_reader
    - file_writer
    - directory_scanner
    - file_monitor
    
  formats:
    - csv_processor
    - json_processor
    - xml_processor
    - binary_processor
    
  cloud_storage:
    - s3_connector
    - azure_blob_connector
    - gcs_connector
    - dropbox_connector

erp_integrations:
  sap:
    - sap_rfc_connector
    - sap_odata_connector
    - sap_bapi_connector
    
  oracle:
    - oracle_ebs_connector
    - oracle_fusion_connector
    
  microsoft:
    - dynamics_365_connector
    - power_platform_connector
    
  salesforce:
    - salesforce_api_connector
    - salesforce_bulk_connector

class ToolsIdentityIntegration:
    def authenticate_tool_access(self, agent_id: str, tool_id: str) -> AuthenticationResult:
        agent_identity = self.identity_service.get_agent_identity(agent_id)
        
        # Verify agent identity
        if not self.identity_service.verify_identity(agent_identity):
            return AuthenticationResult(success=False, reason="identity_verification_failed")
            
        # Check tool permissions
        tool_permissions = self.get_tool_permissions(tool_id)
        agent_permissions = agent_identity.permissions
        
        if not self.check_permission_overlap(tool_permissions, agent_permissions):
            return AuthenticationResult(success=False, reason="insufficient_permissions")
            
        # Generate access token
        access_token = self.generate_access_token(agent_id, tool_id)
        
        return AuthenticationResult(
            success=True,
            access_token=access_token,
            permissions=tool_permissions
        )

class ToolsMemoryIntegration:
    def cache_tool_results_in_memory(self, agent_id: str, tool_result: ToolResult):
        # Store in episodic memory
        episode = Episode(
            timestamp=datetime.utcnow(),
            action=f"tool_execution:{tool_result.tool_id}",
            context=tool_result.context,
            result=tool_result.data,
            success=tool_result.success
        )
        self.memory_system.store_episode(agent_id, episode)
        
        # Update procedural memory if tool usage was successful
        if tool_result.success:
            procedure = Procedure(
                name=f"use_{tool_result.tool_id}",
                parameters=tool_result.parameters,
                context_conditions=tool_result.context,
                success_indicators=tool_result.success_metrics
            )
            self.memory_system.update_procedure(agent_id, procedure)

class ToolsEnvironmentIntegration:
    def adapt_tools_to_environment(self, environment: Environment) -> ToolConfiguration:
        config = ToolConfiguration()
        
        # Adjust based on resource constraints
        if environment.operational.cpu_utilization > 0.8:
            config.execution_timeout = 60  # Reduce timeout under high load
            config.concurrent_limit = 10   # Reduce concurrency
            
        # Adjust based on business constraints
        if environment.business.cost_optimization_mode:
            config.cache_aggressiveness = "high"
            config.retry_attempts = 1
            
        # Adjust based on compliance requirements
        if environment.external.regulatory_compliance.gdpr_required:
            config.data_logging = "minimal"
            config.data_retention = "30_days"
            
        return config

# Check tools system health
sindhan-cli tools health --comprehensive
 
# Test tool connectivity
sindhan-cli tools test-connection --tool-id=<tool_id>
 
# Analyze tool performance
sindhan-cli tools analyze-performance --period=24h
 
# Debug tool execution
sindhan-cli tools debug-execution --execution-id=<exec_id>
 
# Export tools metrics
sindhan-cli tools export-metrics --format=prometheus