acp-sdk-python 1.0.0

Python implementation of the Agent Communication Protocol (ACP)

Agent Communication Protocol (ACP) - Enterprise Agent Communication Protocol

🏢 Enterprise-First Design

Purpose-built for enterprise environments where security, governance, and scale matter most.

ACP (Agent Communication Protocol) is the industry-standard protocol for enterprise-grade agent-to-agent communication. This Python implementation is specifically designed for large organizations deploying multiple AI agents across departments with centralized management and security controls.

Perfect For Enterprise Use Cases:

• 🏛️ Multi-department AI deployments (Sales, Legal, HR, Finance agents)
• 🔐 API Gateway integration (Apigee, Kong, AWS API Gateway)
• 📊 Centralized agent discovery and capability management
• 🛡️ Enterprise security with OAuth 2.0, mTLS, and audit trails
• 📈 Production scale with high-throughput, low-latency communication
• 🎯 Supervisor/Router patterns with specialist agent orchestration

Architecture Highlights:

Router Agent (Supervisor) → API Gateway → Specialist Agents (Servers)
     ↓                           ↓              ↓
Orchestrates workflows    Apigee OAuth2    Department-specific
Multi-agent coordination  Rate limiting    Domain expertise
Central task routing      Security policies Scalable processing

ACP (Agent Communication Protocol) is the industry-standard protocol for secure, scalable agent-to-agent communication. Built on JSON-RPC 2.0, ACP enables AI agents to discover, authenticate, and collaborate across any platform.

🚀 Why ACP for Enterprise?

• 🏛️ Enterprise Standard: Purpose-built for large-scale organizational deployments
• 🔒 Production Security: OAuth2, mTLS, API gateway integration, audit trails
• 🌐 Multi-Cloud Ready: Deploy across AWS, Azure, GCP with consistent protocols
• 📊 Centralized Governance: Agent discovery, capability management, SLA monitoring
• ⚡ Enterprise Scale: High-throughput, low-latency, multi-tenant architecture
• 🎯 Proven Patterns: Router/supervisor architecture with specialist agent coordination

🏢 See Enterprise Deployment Guide for Apigee integration, security patterns, and production deployment.

📦 Quick Start

Installation

pip install acp-python

Basic Client Usage

import acp
from acp.models import TasksCreateParams, Message, Part

# Connect to an agent
client = acp.Client("https://agent.example.com/jsonrpc")

# Send a task
response = await client.tasks.create(TasksCreateParams(
    initialMessage=Message(
        role="user",
        parts=[Part(type="TextPart", content="Search for recent tickets")]
    ),
    priority="HIGH"
))

print(f"Task created: {response.taskId}")

Basic Server Usage

import acp

# Create ACP server
server = acp.Server(
    title="My Agent",
    description="An intelligent assistant agent"
)

@server.method_handler("tasks.create")
async def handle_task(params, context):
    """Handle incoming task requests"""
    # Your agent logic here
    return {
        "type": "task",
        "task": {
            "taskId": "task-123",
            "status": "SUBMITTED",
            "createdAt": "2024-01-01T00:00:00Z"
        }
    }

# Run the server
server.run(host="0.0.0.0", port=8000)

🏗️ Architecture

ACP provides a complete stack for agent communication:

┌─────────────────────────────────────────────────────┐
│                    Your Application                 │
├─────────────────────────────────────────────────────┤
│  📱 ACP Client           🖥️  ACP Server            │
│  • Task Management      • Request Handling          │
│  • Streaming            • Authentication            │
│  • Discovery            • Validation                │
├─────────────────────────────────────────────────────┤
│             🌐 ACP Protocol Layer                   │
│  • JSON-RPC 2.0         • OAuth2 Security          │
│  • Agent Discovery      • Real-time Streaming       │
│  • Error Handling       • Webhook Notifications     │
├─────────────────────────────────────────────────────┤
│                🔧 Transport Layer                   │
│  • HTTPS/TLS            • WebSockets               │
│  • Load Balancing       • Rate Limiting            │
└─────────────────────────────────────────────────────┘

🔧 Core Features

1. Task Management

• Asynchronous Processing: Submit tasks and receive results when ready
• Priority Handling: HIGH, MEDIUM, LOW priority levels
• Progress Tracking: Real-time status updates and notifications
• Artifact Exchange: Secure file and data transfer

2. Real-time Streaming

• Bidirectional Communication: Interactive conversations between agents
• Message Chunking: Efficient handling of large data streams
• Connection Management: Automatic reconnection and error recovery

3. Agent Discovery

• Agent Cards: Standardized capability discovery via /.well-known/agent.json
• Skill Registry: Declare and discover agent capabilities
• Version Management: Semantic versioning for protocol compatibility

4. Enterprise Security

• OAuth2 Authentication: Industry-standard authentication flows
• Scope-based Authorization: Fine-grained permission control
• HTTPS Everywhere: Encrypted transport for all communications
• Token Management: Automatic token refresh and validation

🛠️ CLI Tools

ACP includes professional command-line tools:

# Protocol information
acp schema info              # Show protocol specification
acp schema methods           # List available methods

# Agent discovery
acp agent-card validate      # Validate agent card files
acp agent-card examples      # Show example configurations

# Development tools
acp server start             # Start development server
acp validate request.json    # Validate ACP requests

📚 Documentation

• 📖 Protocol Specification - Complete ACP protocol documentation
• 🚀 Quick Start Guide - Get up and running in 5 minutes
• 📘 API Reference - Complete Python API documentation
• 💡 Examples - Working examples and templates
• 🔧 Development Guide - Build your own ACP agents

🌟 Examples

Example	Description	Link
Basic Client	Simple task submission	View
Basic Server	Handle incoming requests	View
Confluence Agent	Enterprise search agent	View
Streaming Chat	Real-time conversations	View

🏢 Enterprise Features

ACP is designed for production enterprise environments:

• 🎯 High Availability: Load balancing and failover support
• 📊 Observability: Structured logging and metrics collection
• 🔄 Scalability: Horizontal scaling with connection pooling
• 🛡️ Security: Enterprise-grade authentication and authorization
• 📈 Performance: Optimized for high-throughput workloads

🤝 Contributing

ACP is an open protocol welcoming contributions:

1. Protocol: Propose enhancements to the core specification
2. Implementation: Improve the Python reference implementation
3. Documentation: Help make ACP more accessible
4. Testing: Add test cases and improve reliability

See our Contributing Guide for details.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Links

• 🌐 Protocol Website: acp-protocol.org
• 📚 Documentation: docs.acp-protocol.org
• 🐙 GitHub: github.com/acp-protocol
• 💬 Discussions: GitHub Discussions
• 🐛 Issues: GitHub Issues

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Agent Communication Protocol (ACP)
The Standard for Agent-to-Agent Communication

Made with ❤️ by the ACP community