Seamlessly integrate your CrewAI multi-agent systems with ElevenLabs using Klavis AI's comprehensive MCP server connection guide.
ElevenLabs is an AI voice generation platform. Generate realistic speech, clone voices, create audio content, manage voice library, and synthesize multilingual audio via OpenAPI integration
Follow these steps to connect CrewAI to this MCP server
Sign up for KlavisAI to access our MCP server management platform.
Set up your CrewAI agents with the MCP server tools and configure authentication settings for collaborative workflows.
Test your multi-agent workflows and start using your enhanced collaborative AI capabilities.
import os
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType
# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
elevenlabs_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.ELEVENLABS,
user_id="1234",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
with MCPServerAdapter(elevenlabs_mcp_instance.server_params) as mcp_tools:
# Create a ElevenLabs Analysis Agent
elevenlabs_agent = Agent(
role="ElevenLabs Analyst",
goal="Research and analyze elevenlabs to extract comprehensive insights",
backstory="You are an expert at analyzing elevenlabs and creating professional summaries.",
tools=mcp_tools,
reasoning=True,
verbose=False
)
# Define Task
analysis_task = Task(
description=f"Research and analyze elevenlabs data. Extract relevant information and create a comprehensive summary with key points and main takeaways.",
expected_output="Complete analysis with structured summary, key insights, and main takeaways",
agent=elevenlabs_agent,
markdown=True
)
# Create and execute the crew
elevenlabs_crew = Crew(
agents=[elevenlabs_agent],
tasks=[analysis_task],
verbose=False,
process=Process.sequential
)
result = elevenlabs_crew.kickoff()
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