Why Agent Kernel?
Built for developers who need flexibility without sacrificing power
Framework Agnostic
Build agents using any AI agentic framework and migrate them to Agent Kernel to benefit from its execution framework capabilities. No vendor lock-in - seamlessly migrate between LangGraph, OpenAI Agents SDK, Google ADK, CrewAI, and custom frameworks without rewriting your agent logic.
Production Ready
Enterprise-grade features including built-in session management, conversational state tracking, pluggable memory backends, comprehensive traceability with LangFuse and OpenLLMetry, and multi-agent collaboration support. Deploy with confidence from day one.
Deploy Anywhere
From CLI testing for local development to REST API servers, AWS serverless, containerized environments, or on-premise deployments. One codebase, multiple deployment options. Switch deployment modes without changing your agent code.
Versatile Integrations
Built-in integrations for popular messaging platforms including Slack, WhatsApp, Messenger, Instagram, and Telegram. Support for MCP Server and A2A Server protocols. Easy-to-build custom integrations with pluggable architecture.
Core Features
Everything you need to build sophisticated AI agents
Agent Design & Definition
Define agents with clear roles, capabilities, and behaviors using intuitive Python APIs. All framework adapters expose the same core abstractions: Agent, Runner, Session, Module, and Runtime.
- Python-first SDK
- Unified API across frameworks
- Role-based design
- Flexible configuration
Tool Integration
Bind custom tools, APIs, and functionalities to your agents for enhanced capabilities. Publish tools via MCP Server for Model Context Protocol integration.
- Custom tool support
- API integrations
- MCP tool publishing
- Pluggable architecture
Hierarchies & Collaboration
Create agent teams with complex topologies, hierarchies, and collaborative workflows.
- Multi-agent systems
- Agent hierarchies
- Collaborative patterns
Context & Memory
Efficient memory management with support for in-memory, Redis, and DynamoDB backends.
- Multiple memory stores
- Context preservation
- Custom adapters
Execution Hooks
Customize agent behavior with pre and post-execution hooks for guardrails, RAG, and response moderation.
- Pre-execution hooks
- Post-execution hooks
- Context injection
Fault Tolerance
Production-grade resilience with multi-AZ deployments, automatic failure recovery, and health monitoring for high availability.
- Multi-AZ deployment
- Auto-recovery
- Health monitoring
- Zero downtime
Traceability & Observability
Comprehensive tracking of agent actions, LLM calls, and collaborative operations.
- LangFuse integration
- OpenLLMetry support
- Multi-level verbosity
MCP & A2A Support
Built-in Multi-Context Processing and Agent-to-Agent communication capabilities.
- MCP integration
- A2A messaging
- Cross-agent coordination
Framework Support
Work with your favorite agentic frameworks
OpenAI Agents SDK
Full support for OpenAI's agentic framework with seamless integration.
Learn more →LangGraph
Build stateful, multi-actor applications with LangChain's graph framework.
Learn more →Google ADK
Leverage Google's Agent Development Kit for advanced agent capabilities.
Learn more →CrewAI
Orchestrate role-playing autonomous AI agents for complex tasks.
Learn more →Memory Management
Pluggable memory architecture with flexible backends for every use case. Choose the right storage solution for your development, testing, and production needs.
In-Memory
Fast, ephemeral storage for development and testing
- Local development
- Testing
- Prototyping
Redis
High-performance distributed memory for production workloads
- Production systems
- Shared state
- High throughput
DynamoDB
Serverless, scalable NoSQL database for AWS deployments
- Serverless apps
- AWS environments
- Global scale
Custom Adapters
Build your own memory backend for specific requirements
- Enterprise systems
- Custom databases
- Special needs
Testing & Development
Built-in agent test framework for local development. Focus on domain-specific agent development while Agent Kernel takes care of testing, deployment, and execution.
CLI-Based Testing
Interactive command-line interface for real-time agent testing and debugging. Test your agents in a controlled environment before deployment.
- Interactive chat sessions
- Real-time feedback
- Easy debugging
- Local execution
Automated Test Framework
Execute predefined test scenarios to validate agent behavior consistently. Build comprehensive test suites for your agentic systems.
- Scenario-based testing
- Automated validation
- Regression testing
- CI/CD integration
Deployment Options
Ready-to-use execution capabilities for every environment. Deploy anywhere, from local development to global scale production, without changing your agent code.
Local Development
Test and develop agents locally with the built-in Agent Tester utility.
- CLI-based interaction
- Automated test scenarios
- Rapid iteration
- No cloud dependencies
AWS Serverless
Scale dynamically with serverless architecture for variable workloads.
- Lambda-based execution
- Auto-scaling
- Pay-per-use pricing
- Zero infrastructure management
AWS Containerized
Consistent performance with container-based deployment on AWS.
- ECS/EKS support
- Lower latency
- Predictable performance
- Resource optimization
On-Premise / Docker
Deploy in your own infrastructure with REST API and Docker support.
- Full control
- Docker containerization
- REST API included
- Custom infrastructure
Infrastructure as Code
Deploy with confidence using our official Terraform modules. One-command deployment to AWS with best practices baked in.
View Terraform ModulesObservability & Traceability
Complete visibility into agent operations
Multi-Level Traceability
Track every action, decision, and LLM call with configurable verbosity levels.
- Agent action tracking
- LLM call monitoring
- Collaborative operation logs
- Performance metrics
Integrated Observability Tools
LangFuse
Comprehensive LLM observability and analytics platform
TraceLoop OpenLLMetry
OpenTelemetry-based observability for LLM applications
Messaging Integrations
Connect your AI agents to popular messaging platforms and reach your users where they are. Built-in integrations for Slack, WhatsApp, Messenger, Instagram, and Telegram.
Ready to Build Your AI Agents?
Agent Kernel is ideal for AI engineers who want framework flexibility, teams building production AI agent systems, developers migrating between frameworks, organizations requiring enterprise-grade deployment, and researchers exploring different agent frameworks.
Get started with Agent Kernel today and bring your agentic applications to production.