Composiohq Composio Building Agents Using Crewai

Building Agents using CrewAI with Composio

Build multi-agent teams using CrewAI with Composio Tool Router.

Installation

pip install composio-crewai crewai crewai-tools

Find Latest Versions:

pip index versions crewai | grep "Available versions" | head -1
pip index versions composio-crewai | grep "Available versions" | head -1

Integration Method

CrewAI is an agentic provider - use MCP for multi-agent teams.

MCP Integration

from crewai import Agent, Task, Crew
from crewai.mcp import MCPServerHTTP
from composio import Composio

composio = Composio()

def create_crew(user_id: str):
    # Create session
    session = composio.create(user_id=user_id, toolkits=["github"])

    # Create agent with MCP server
    agent = Agent(
        role="GitHub Manager",
        goal="Manage GitHub repositories",
        backstory="You are an expert at GitHub operations",
        mcps=[
            MCPServerHTTP(
                url=session.mcp.url,
                headers=session.mcp.headers
            )
        ]
    )

    # Define task
    task = Task(
        description="Create a GitHub issue titled 'Bug Report'",
        expected_output="Confirmation of issue creation",
        agent=agent
    )

    # Execute crew
    crew = Crew(agents=[agent], tasks=[task])
    return crew

crew = create_crew("user_123")
result = crew.kickoff()
print(result)

Multi-Agent Team Example

from crewai import Agent, Task, Crew, Process
from crewai.mcp import MCPServerHTTP
from composio import Composio

composio = Composio()

def create_team(user_id: str):
    session = composio.create(user_id=user_id, toolkits=["github", "slack"])

    # Create MCP server connection
    mcp_server = MCPServerHTTP(
        url=session.mcp.url,
        headers=session.mcp.headers
    )

    # Create specialized agents
    researcher = Agent(
        role="GitHub Researcher",
        goal="Analyze repositories",
        backstory="Expert at code analysis",
        mcps=[mcp_server]
    )

    reporter = Agent(
        role="Report Writer",
        goal="Create reports",
        backstory="Expert at documentation",
        mcps=[mcp_server]
    )

    # Define tasks
    research_task = Task(
        description="Analyze the repository",
        expected_output="Analysis report",
        agent=researcher
    )

    report_task = Task(
        description="Create a summary report",
        expected_output="Markdown report",
        agent=reporter,
        context=[research_task]
    )

    crew = Crew(
        agents=[researcher, reporter],
        tasks=[research_task, report_task],
        process=Process.sequential
    )

    return crew

team = create_team("user_123")
result = team.kickoff()

Key Features

• Multi-Agent Teams: Agents collaborate on tasks
• Task Dependencies: Sequential or hierarchical execution
• YAML Configs: Clean agent/task definitions
• Production Ready: Mature framework

Key Resources

• CrewAI Docs: https://docs.crewai.com/
• Tool Router Guide: /building-agents
• Quickstart: https://docs.crewai.com/en/quickstart
• GitHub: https://github.com/crewAIInc/crewAI

Environment Variables

OPENAI_API_KEY=sk-...  # Or other LLM provider
COMPOSIO_API_KEY=...

Next Steps

1. Use /building-agents for comprehensive guide
2. Check python/providers/crewai/ for complete examples
3. See CrewAI docs for multi-agent patterns