agentcore-sdk 0.1.1

Open-source orchestration framework for agentic AI systems with multi-agent coordination, tool integration, and workflow management

AgentCore

Production-ready orchestration framework for agentic AI systems implementing Google's A2A (Agent-to-Agent) protocol v0.2.

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Features

A2A Protocol Implementation

• JSON-RPC 2.0 compliant API for standardized agent communication
• Agent discovery via /.well-known/agent.json endpoints
• Task coordination with full lifecycle management
• Real-time messaging via WebSocket and Server-Sent Events (SSE)
• Distributed tracing with A2A context propagation

Agent Runtime

• Chain-of-Thought (CoT) reasoning engine
• ReAct pattern for iterative reasoning and action
• Autonomous execution mode for complex multi-step tasks
• Multi-tool integration with API connectors, code execution, and file operations
• Plugin system with version management and validation
• State persistence with backup and recovery
• Sandbox execution with security profiles

Memory Service

• Hierarchical memory with working, episodic, and semantic layers
• Entity-Centric Learning (ECL) pipeline for knowledge extraction
• Graph-based memory with Neo4j integration
• Hybrid search combining vector similarity and graph traversal
• MEMify optimization for memory consolidation and pruning
• Context compression and expansion for efficient token usage

LLM Client Service

• Multi-provider support: OpenAI, Anthropic, Google Gemini
• Intelligent model selection based on task requirements
• Automatic failover with provider health monitoring
• Cost tracking and budget management
• Response caching for optimization

ACE (Adaptive Capability Engine)

• Performance monitoring with baseline tracking
• Capability evaluation and fitness scoring
• Intervention engine with trigger-based decisions
• Playbook management for automated responses
• Delta generation for capability improvements

DSPy Optimization

• MIPROv2 and GEPA optimization algorithms
• MLflow integration for experiment tracking
• A/B testing framework for prompt variants
• Continuous learning with drift detection
• GPU acceleration support

Coordination Service

• Multi-agent coordination with consensus protocols
• Workflow orchestration with graph-based execution
• CQRS pattern with event sourcing
• Saga pattern for distributed transactions
• Parallel execution with dependency resolution

Integration Layer

• Cloud storage: S3, GCS, Azure Blob
• Database connectors: PostgreSQL with async support
• Webhook management with delivery tracking
• Resilience patterns: Circuit breaker, bulkhead, timeout
• Security: Credential management, compliance scanning

Training System

• GRPO (Group Relative Policy Optimization)
• Trajectory recording and replay
• Custom reward registry
• Credit assignment algorithms
• Job management with budget controls

CLI

• 4-layer architecture: CLI, Service, Protocol, Transport
• Agent management: register, list, info, remove
• Task operations: create, list, status tracking
• Session management: create, list, pause
• Workflow control: start, monitor, manage
• Configuration: show, set, validate

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Quick Start

Prerequisites

• Python 3.12+
• PostgreSQL 14+
• Redis 7+
• Neo4j 5+ (optional, for graph memory)

Installation

# Clone the repository
git clone https://github.com/Mathews-Tom/AgentCore.git
cd AgentCore

# Install dependencies using uv
uv sync

# Set up environment
cp .env.test.template .env

Running with Docker Compose

# Start all services
docker compose -f docker-compose.dev.yml up

# API available at http://localhost:8001
# API docs at http://localhost:8001/docs

Running Locally

# Start database and Redis
docker compose -f docker-compose.dev.yml up postgres redis

# Apply migrations
uv run alembic upgrade head

# Start development server
uv run uvicorn agentcore.a2a_protocol.main:app --host 0.0.0.0 --port 8001 --reload

CLI Usage

# Register an agent
agentcore agent register --name "my-agent" --capabilities "text_generation,analysis"

# List agents
agentcore agent list

# Create a task
agentcore task create --description "Analyze customer feedback"

# Start a session
agentcore session create --name "analysis-session"

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Architecture

src/agentcore/
├── a2a_protocol/          # A2A protocol implementation
│   ├── models/            # Pydantic models (AgentCard, Task, Event)
│   ├── services/          # Business logic and JSON-RPC handlers
│   ├── routers/           # FastAPI endpoints
│   └── database/          # PostgreSQL models and repositories
│
├── agent_runtime/         # Agent execution engine
│   ├── engines/           # CoT, ReAct, Autonomous engines
│   ├── services/          # Lifecycle, tools, state management
│   └── tools/             # Built-in and custom tool support
│
├── ace/                   # Adaptive Capability Engine
│   ├── capability/        # Evaluation and scoring
│   ├── intervention/      # Trigger-based decisions
│   └── monitors/          # Performance tracking
│
├── dspy_optimization/     # DSPy optimization framework
│   ├── algorithms/        # MIPROv2, GEPA
│   ├── learning/          # Continuous learning, drift detection
│   └── tracking/          # MLflow integration
│
├── gateway/               # API gateway services
├── integration/           # External service integrations
├── orchestration/         # Workflow orchestration (CQRS, Saga)
├── reasoning/             # Reasoning strategies
└── training/              # RL training system

src/agentcore_cli/         # Command-line interface
├── commands/              # CLI command handlers
├── services/              # Service layer
├── protocol/              # JSON-RPC client
└── transport/             # HTTP transport

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Testing

# Run all tests
uv run pytest

# Run with coverage report
uv run pytest --cov=src --cov-report=html

# Run specific test categories
uv run pytest tests/unit/
uv run pytest tests/integration/
uv run pytest tests/cli/

# Load testing
uv run locust -f tests/load/locustfile.py

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Development

# Install dev dependencies
uv sync --dev

# Run linter
uv run ruff check src/ tests/

# Auto-fix issues
uv run ruff check --fix src/ tests/

# Type checking
uv run mypy src/

Database Migrations

# Create migration
uv run alembic revision --autogenerate -m "description"

# Apply migrations
uv run alembic upgrade head

# Rollback
uv run alembic downgrade -1

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Configuration

All settings via environment variables or .env:

# Database
DATABASE_URL=postgresql+asyncpg://user:pass@host:5432/agentcore

# Redis
REDIS_URL=redis://localhost:6379/0

# Security
JWT_SECRET_KEY=your-secret-key
JWT_ALGORITHM=HS256

# LLM Providers
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
GOOGLE_API_KEY=AI...

# Monitoring
ENABLE_METRICS=true
LOG_LEVEL=INFO

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Documentation

• API Reference - JSON-RPC method specifications
• Architecture - System design documents
• CLI Reference - Command-line interface guide
• Deployment - Production deployment guides
• Security - Security audit and compliance

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License

AGPL-3.0 License - see LICENSE for details.