Integrations Overview

Agent Kernel provides various built in integrations to connect your AI agents with external platforms and services. These integrations allow you to deploy your agents in real-world environments and interact with users through different channels.

API

For API custom integrations you can implement RESTRequestHandler and pass it to the RESTAPI.run() method.

from fastapi import APIRouter
from agentkernel.api import RESTRequestHandler
from agentkernel.api import RESTAPI
from agentkernel.slack import AgentSlackRequestHandler

class CustomHandler(RESTRequestHandler):
  def get_router(self) -> APIRouter:
      """
        - GET /health: Health check
        - GET /agents: List available agents
      """
      router = APIRouter()

      @router.get("/health")
      def health():
          return {"status": "ok"}

      @router.get("/agents")
      def list_agents():
          return {"agents": list(Runtime.instance().agents().keys())}

      @router.get("/rag_agent")
      def handle_rag(req: Request):
          return self._handler(req)

  def _handler(req):
      # Do a vector search and return something

if __name__ == "__main__":
    RESTAPI.run([ AgentSlackRequestHandler(), CustomHandler()]) # Can pass multiple handlers

Available Integrations

Collaboration Platforms

• Slack - Deploy agents as Slack bots that can respond to mentions and direct messages in Slack workspaces
• WhatsApp - Deploy agents as WhatsApp bots
• Messenger - Deploy agents as FB Messenger bots

Observability & Monitoring

• Langfuse - Open-source LLM engineering platform for tracing, evaluating, and monitoring AI applications. See Traceability and Observability for detailed setup and usage.
• OpenLLMetry (Traceloop) - OpenTelemetry-based observability for LLM applications with support for multiple backends including Traceloop, Datadog, New Relic, and Honeycomb. See Traceability and Observability for detailed setup and usage.