How to Use the CAMB.AI MCP in CrewAI

Q: How would a CrewAI team collaborate on a CAMB.AI translation job?

One agent initiates the job with createdubbing and gets a task ID. It then passes that ID to another agent through CrewAI's shared context. The second agent can then take over, using the ID with getjobstatus to monitor the job to completion.

Q: What's the best way to pass a CAMB.AI task ID between agents in CrewAI?

The agent that calls createdubbing or createtts should return the resulting task ID in its output. The next agent in the sequence can then access that output from the shared context and use it as an input for its own tasks.

Deploy autonomous agent crews that use the CAMB.AI MCP server to translate and generate audio with CrewAI.

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Connect CAMB.AI MCP to CrewAI

Create your Vinkius account to connect CAMB.AI to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup CAMB.AI with CrewAI

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A Crew for Global Content Ops

Assemble a specialized team of agents for your media pipeline. A 'Scout' agent can monitor a source for new videos. When it finds one, it tasks a 'Translator' agent to use the `create_dubbing` tool from the CAMB.AI MCP server. The 'Translator' agent works the job, polling `get_job_status` until it's done. Once complete, it passes the URL of the dubbed audio to a 'Publisher' agent, whose only job is to upload the final product. Each agent has one role, and the crew gets the job done without you.

Build a Voice Generation Pipeline

Chain agents together to turn scripts into finished audio. An 'Author' agent writes the copy. It hands the text off to a 'Voice Director' agent, which analyzes the text and selects the best voice from `list_voices`. Then, the 'Voice Director' tasks a 'Sound Engineer' agent to generate the audio using `create_tts`. Because CrewAI agents share context, the task ID from CAMB.AI can be passed between them, allowing one agent to start the job and another to pick up the result.

Autonomous Voice Brand Management

Assign an agent to be the guardian of your brand's sound. This 'Voice Auditor' agent can have a recurring task to run `list_cloned_voices` and compare it against a master list of approved voices. It can flag any discrepancies. If a new voice is needed for a campaign, a different agent can be tasked to use `create_voice_clone` to produce it. This MCP connection makes the crew completely self-sufficient in managing its own audio assets.

Setup guide

Set up CAMB.AI MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke CAMB.AI tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="CAMB.AI Analyst",
    goal="Access and analyze CAMB.AI data via MCP.",
    backstory="Expert analyst with direct CAMB.AI access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent CAMB.AI transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="CAMB.AI Analyst",
        goal="Access and analyze CAMB.AI data via MCP.",
        backstory="Expert analyst with direct CAMB.AI access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent CAMB.AI transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CAMB.AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about CAMB.AI MCP in CrewAI

Yes. When you configure your CrewAI agent, you can provide a list of specific tools it's allowed to use. This lets you create a specialist 'Translator' agent that only has access to `create_dubbing` and `get_job_status` from the CAMB.AI server.

One agent initiates the job with `create_dubbing` and gets a task ID. It then passes that ID to another agent through CrewAI's shared context. The second agent can then take over, using the ID with `get_job_status` to monitor the job to completion.

No, authentication is handled by the connection string. You pass the secure Vinkius URL to your CrewAI agent configuration, and it handles the rest. Your agents just focus on using the tools.

The agent that calls `create_dubbing` or `create_tts` should return the resulting task ID in its output. The next agent in the sequence can then access that output from the shared context and use it as an input for its own tasks.

They're discarded. Vinkius processes all MCP server jobs in ephemeral, single-use environments. The source audio you provide for a dubbing or voice cloning job is deleted from the temporary file system as soon as the task is complete.

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