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Agent Kernel

The Operating System for Scalable & Compliant Enterprise AI Agents

Run, orchestrate, and deploy production AI agents at scale β€” across frameworks and clouds β€” without lock-in, rewrites, or fragile glue code.

PyPI License: Apache 2.0 Discord GitHub stars

πŸ“– Docs β€’ πŸš€ Quick Start β€’ ✨ Features β€’ ☁️ Deploy β€’ πŸ’¬ Discord β€’ πŸ›  Developer Guide


Why Agent Kernel?

Most agent frameworks help you build a prototype. Agent Kernel is the platform layer that gets you to production β€” with the governance, portability, and operational maturity that enterprises actually require.

Agent Kernel
πŸ”Œ Framework-Agnostic Run OpenAI Agents SDK, LangGraph, CrewAI, and Google ADK side by side. Swap with 2 import lines.
☁️ Cloud-Agnostic The same agent code ships to AWS Lambda/ECS, Azure Functions/Container Apps, GCP (soon), or on-prem.
πŸ›‘οΈ Compliant by Default Built-in guardrails (OpenAI, AWS Bedrock), PII detection, full audit traces, jailbreak prevention.
🧠 Stateful & Knowledge-Aware Pluggable session stores (Redis, DynamoDB, Cosmos DB) + knowledge bases (ChromaDB, Neo4j, Starburst).
πŸ’¬ Channels Built-In Slack, WhatsApp, Teams, Telegram, Gmail, Messenger, Instagram β€” out of the box.
πŸ” Production Observability LangFuse and OpenLLMetry tracing wired in. Every agent, tool, and LLM call β€” visible.
🀝 Open Standards Native MCP (Model Context Protocol) and A2A (Agent-to-Agent) support.
πŸ†“ Apache 2.0 No licensing fees. No vendor lock-in. Production-ready open source.

⭐ If Agent Kernel is solving real problems for you, please star the repo β€” it's the single best way to help us grow.


πŸš€ Quick Start

Requirements: Python 3.12 – 3.13.x

pip install agentkernel

Build a multi-agent system that runs on OpenAI Agents SDK today and LangGraph tomorrow β€” same code:

from agentkernel.cli import CLI
from agentkernel.openai import OpenAIModule
from agents import Agent

math_agent = Agent(
    name="math",
    handoff_description="Specialist agent for math questions",
    instructions="You provide help with math problems.",
)

general_agent = Agent(
    name="general",
    handoff_description="Agent for general questions",
    instructions="You provide assistance with general queries.",
)

triage_agent = Agent(
    name="triage",
    instructions="You determine which agent to use based on the user's question.",
    handoffs=[general_agent, math_agent],
)

module = OpenAIModule([triage_agent, math_agent, general_agent])

if __name__ == "__main__":
    CLI.main()

That's it. Same code deploys to AWS Lambda, ECS, Azure Functions, or Container Apps with a single Terraform module. πŸ‘‰ Get Started


✨ Features

🧩 Works with the Frameworks You Already Use

OpenAI Agents SDK Β β€’Β  LangGraph Β β€’Β  CrewAI Β β€’Β  Google ADK Β β€’Β  Smol Agents (soon) Β β€’Β  LiveKit (soon)

No rewrites. No re-learning. Bring your agents β€” Agent Kernel handles the platform layer.

πŸ›‘οΈ Compliance & Governance β€” First-Class, Not an Afterthought

Enterprises can't ship agents they can't audit. Agent Kernel makes compliance the default:

  • Guardrails β€” OpenAI and AWS Bedrock guardrails for PII detection, jailbreak prevention, content moderation.
  • Pre/Post Execution Hooks β€” Inject policy checks, RAG context, redaction, or moderation around every agent call.
  • Full Traceability β€” Every agent action, tool call, and LLM invocation logged with configurable verbosity.
  • Observability β€” LangFuse and OpenLLMetry tracing with a single config line.
  • Data Residency β€” Pick your cloud, your region, your storage backend. Your data stays where you need it.

🧠 Memory, Sessions & Knowledge Bases

Layer Backends
Session / Memory In-memory, Redis, DynamoDB (AWS), Cosmos DB (Azure)
Vector Knowledge ChromaDB
Graph Knowledge Neo4j
SQL Analytics Starburst Galaxy (Trino)
Custom Pluggable KnowledgeBase interface β€” bring any backend

πŸ’¬ Messaging Channels β€” Out of the Box

Slack β€’ WhatsApp β€’ Microsoft Teams β€’ Telegram β€’ Gmail β€’ Messenger β€’ Instagram

Build once. Ship to every channel your users live on. No bespoke bot code.

πŸ”Œ Open Protocols

  • MCP (Model Context Protocol) β€” Connect agents to external tools, data sources, and services. Optionally expose your agents as MCP tools.
  • A2A (Agent-to-Agent) β€” Native message passing, handoffs, and coordination between agents in a shared ecosystem.

⚑ Built-In Execution Modes

  • Synchronous β€” Classic request/response.
  • WebSocket / Async β€” Streaming, long-running, real-time agent interactions.
  • Stateless MCP β€” Lightweight agent-as-tool deployments.

☁️ Deploy Anywhere

Same agent code. Pick your runtime. Full Terraform modules included.

Cloud Serverless Containerized
AWS Lambda ECS / Fargate
Azure Functions Container Apps
GCP Coming soon Coming soon
On-Prem βœ… Docker image βœ… REST API bundle

πŸ›  Agent Skills β€” Supercharge Your Coding Assistant

Install Agent Kernel skills and Claude, Copilot, Cursor, or Windsurf become experts at building production agents β€” no hallucinated APIs.

ak skill install
Skill What it does
ak-init Scaffold a new project β€” any framework, any deployment mode
ak-build Add tools, agents, handoffs β€” context-aware and framework-specific
ak-add-capabilities Wire in guardrails, tracing, sessions, MCP, A2A, hooks, multimodal
ak-add-integration Slack, WhatsApp, Messenger, Instagram, Telegram, Gmail
ak-cloud-deploy AWS Lambda, ECS, Azure Functions, Container Apps with full Terraform
ak-test Fuzzy, judge, and fallback test modes + a debugging playbook

πŸ§ͺ Testing β€” pytest-Integrated

pytest tests/

Built-in fuzzy, semantic, and fallback comparison modes. CI/CD ready. Test agent behavior, not just code.


πŸ‘₯ Who's It For?

  • AI Startups β€” Go from prototype to production in days, not quarters.
  • Software Product Companies β€” Add intelligent agents to your SaaS without framework lock-in.
  • Software Services Companies β€” Ship client agent solutions in weeks, not months.
  • Domain Experts β€” Build production AI products without a full platform engineering team.
  • Regulated Enterprises β€” Get compliance, traceability, and data residency by default.

🌐 Affiliations

Agent Kernel is proud to be:


πŸ’¬ Community & Support


License

Unless otherwise specified, all content β€” including all source and documentation files in this repository β€” is:

Copyright (c) 2025-2026 Yaala Labs.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

SPDX-License-Identifier: Apache-2.0

About

The Operating System for Scalable Enterprise AI Agents - Run, orchestrate, and deploy Compliant Enterprise AI Agents at scale across frameworks, without lock-in, rewrites or fragile glue code. Native support for MCP, A2A. Interface with all mainstream communication channels seamlessly out of the box, production ready from day one.

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