Agentic AI Development

Build intelligent AI agents that can reason, plan, and coordinate using the PHP MCP SDK. This section covers everything you need to create sophisticated AI systems.

What are Agentic AI Systems?

Agentic AI systems are intelligent agents that can:

Reason about problems and make decisions
Plan multi-step workflows to achieve goals
Coordinate with other agents and systems
Learn from interactions and improve over time

Core Concepts

Agent Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   LLM Core      │◄──►│  Agent Logic    │◄──►│  MCP Tools      │
│   (Reasoning)   │    │  (Planning)     │    │  (Actions)      │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│    Memory       │    │  Goal Tracking  │    │   External      │
│   (Context)     │    │   (State)       │    │   Systems       │
└─────────────────┘    └─────────────────┘    └─────────────────┘

Key Components

Reasoning Engine: LLM that makes decisions
Planning System: Breaks down complex goals
Tool Orchestration: Coordinates MCP tool usage
Memory Management: Maintains context and state
Goal Tracking: Monitors progress and adapts

Agent Examples

Building AI Agents

Learn to create intelligent agents with:

Decision-making logic
Goal-oriented behavior
Context awareness
Error recovery

Multi-Agent Systems

Coordinate multiple specialized agents:

Role-based task distribution
Inter-agent communication
Conflict resolution
Collaborative problem-solving

Agent Orchestration

Advanced coordination patterns:

Workflow management
Resource allocation
Performance optimization
Scaling strategies

Real-World Applications

Personal Assistant Agent

An AI agent that can:

Manage calendars and schedules
Send emails and messages
Research information
Make reservations

php

class PersonalAssistantAgent extends Agent
{
    public function processRequest(string $request): AgentResponse
    {
        $intent = $this->analyzeIntent($request);

        return match($intent->type) {
            'schedule' => $this->handleScheduling($intent),
            'research' => $this->handleResearch($intent),
            'communication' => $this->handleCommunication($intent),
            default => $this->handleGeneral($intent)
        };
    }
}

Code Review Agent

Specialized agent for code analysis:

Static code analysis
Security vulnerability detection
Performance optimization suggestions
Code style enforcement

Data Analysis Agent

Intelligent data processing:

Automated report generation
Pattern recognition
Anomaly detection
Predictive analytics

Agent Patterns

Rule-Based Agents

Simple agents that follow predefined rules:

php

class RuleBasedAgent extends Agent
{
    private array $rules;

    public function decide(Context $context): Action
    {
        foreach ($this->rules as $rule) {
            if ($rule->matches($context)) {
                return $rule->getAction();
            }
        }

        return new DefaultAction();
    }
}

Goal-Oriented Agents

Agents that work towards specific objectives:

php

class GoalOrientedAgent extends Agent
{
    private Goal $currentGoal;
    private Planner $planner;

    public function act(): Action
    {
        if ($this->currentGoal->isComplete()) {
            $this->currentGoal = $this->getNextGoal();
        }

        $plan = $this->planner->createPlan($this->currentGoal);
        return $plan->getNextAction();
    }
}

Learning Agents

Agents that improve through experience:

php

class LearningAgent extends Agent
{
    private Memory $memory;
    private LearningAlgorithm $learner;

    public function learn(Experience $experience): void
    {
        $this->memory->store($experience);
        $this->learner->updateModel($experience);
    }
}

Tools for Agents

Planning Tools

Goal decomposition
Task scheduling
Resource allocation
Constraint satisfaction

Memory Tools

Context storage and retrieval
Knowledge base management
Experience logging
Pattern recognition

Communication Tools

Inter-agent messaging
Human interaction
External API integration
Event publishing

Advanced Topics

Multi-Agent Coordination

Agent discovery and registration
Task distribution algorithms
Conflict resolution strategies
Performance monitoring

Agent Security

Access control and permissions
Input validation and sanitization
Audit logging and monitoring
Secure communication protocols

Performance Optimization

Caching strategies
Parallel processing
Resource management
Scalability patterns

Getting Started

Basic Agent Tutorial - Create your first AI agent
Working Examples - Study complete implementations
Best Practices - Learn proven patterns
Community Examples - Share and learn

Tools and Libraries

Required Dependencies

bash

composer require dalehurley/php-mcp-sdk
composer require openai-php/client  # For LLM integration

Optional Enhancements

bash

composer require predis/predis       # For memory/caching
composer require monolog/monolog     # For logging
composer require symfony/messenger   # For async processing

Community

Join the growing community of agentic AI developers:

Ready to build intelligent agents? Start with Building AI Agents! 🤖

Agentic AI Development ​

What are Agentic AI Systems? ​

Core Concepts ​

Agent Architecture ​

Key Components ​

Agent Examples ​

Building AI Agents ​

Multi-Agent Systems ​

Agent Orchestration ​

Real-World Applications ​

Personal Assistant Agent ​

Code Review Agent ​

Data Analysis Agent ​

Agent Patterns ​

Rule-Based Agents ​

Goal-Oriented Agents ​

Learning Agents ​

Tools for Agents ​

Planning Tools ​

Memory Tools ​

Communication Tools ​

Advanced Topics ​

Multi-Agent Coordination ​

Agent Security ​

Performance Optimization ​

Getting Started ​

Tools and Libraries ​

Required Dependencies ​

Optional Enhancements ​

Community ​