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Integration tools let your agents hand off work to other automation platforms and managed AI services. Use them when a workflow needs to invoke an existing CrewAI deployment or delegate specialised tasks to providers such as Amazon Bedrock.

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Available Tools

Merge Agent Handler Tool

Securely access hundreds of third-party tools like Linear, GitHub, Slack, and more through Merge’s unified API.

CrewAI Run Automation Tool

Invoke live CrewAI Platform automations, pass custom inputs, and poll for results directly from your agent.

Bedrock Invoke Agent Tool

Call Amazon Bedrock Agents from your crews, reuse AWS guardrails, and stream responses back into the workflow.

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Common Use Cases

  • Chain automations: Kick off an existing CrewAI deployment from within another crew or flow
  • Enterprise hand-off: Route tasks to Bedrock Agents that already encapsulate company logic and guardrails
  • Hybrid workflows: Combine CrewAI reasoning with downstream systems that expose their own agent APIs
  • Long-running jobs: Poll external automations and merge the final results back into the current run

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Quick Start Example

from crewai import Agent, Task, Crew
from crewai_tools import InvokeCrewAIAutomationTool
from crewai_tools.aws.bedrock.agents.invoke_agent_tool import BedrockInvokeAgentTool

# External automation
analysis_automation = InvokeCrewAIAutomationTool(
    crew_api_url="https://analysis-crew.acme.crewai.com",
    crew_bearer_token="YOUR_BEARER_TOKEN",
    crew_name="Analysis Automation",
    crew_description="Runs the production-grade analysis pipeline",
)

# Managed agent on Bedrock
knowledge_router = BedrockInvokeAgentTool(
    agent_id="bedrock-agent-id",
    agent_alias_id="prod",
)

automation_strategist = Agent(
    role="Automation Strategist",
    goal="Orchestrate external automations and summarise their output",
    backstory="You coordinate enterprise workflows and know when to delegate tasks to specialised services.",
    tools=[analysis_automation, knowledge_router],
    verbose=True,
)

execute_playbook = Task(
    description="Run the analysis automation and ask the Bedrock agent for executive talking points.",
    agent=automation_strategist,
)

Crew(agents=[automation_strategist], tasks=[execute_playbook]).kickoff()

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Best Practices

  • Secure credentials: Store API keys and bearer tokens in environment variables or a secrets manager
  • Plan for latency: External automations may take longer—set appropriate polling intervals and timeouts
  • Reuse sessions: Bedrock Agents support session IDs so you can maintain context across multiple tool calls
  • Validate responses: Normalise remote output (JSON, text, status codes) before forwarding it to downstream tasks
  • Monitor usage: Track audit logs in CrewAI Platform or AWS CloudWatch to stay ahead of quota limits and failures