How to Use the api.video MCP in CrewAI

Q: How do I filter api.video tools for CrewAI agents?

Use the toolfilter option in your agent setup. You can limit which tools each agent can access for better security.

Q: Are api.video analytics available to CrewAI teams?

The agents can call getvideoanalytics to pull performance data. This allows them to report on video reach automatically.

Q: Can CrewAI delete api.video content?

Agents can use deletevideo if you authorize them. We recommend using a moderator agent to confirm deletions before they happen.

Deploy autonomous video operations with CrewAI agents working in collaborative teams.

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Connect api.video MCP to CrewAI

Create your Vinkius account to connect api.video 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 api.video with CrewAI

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CrewAI Autonomous Video Operations

Assign a researcher agent to `list_videos` and a technical agent to `update_video_details`. They share memory to keep your library updated. This removes the need for manual oversight. Your crew manages the video lifecycle from creation to metadata maintenance.

Specialized Video Monitoring for CrewAI

Set a moderator agent to run `get_video_analytics` periodically. If performance dips, it triggers a second agent to check player themes. Your agents act as a team. They identify issues and apply fixes without you touching the code.

Structured Content Handling in CrewAI

Use `list_video_chapters` and `list_video_captions` to feed your documentation agents. They extract information and summarize video content for your team. This keeps your internal knowledge base current. The agents update the records whenever new video content is detected.

Setup guide

Set up api.video 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 api.video tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent api.video 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="api.video Analyst",
        goal="Access and analyze api.video data via MCP.",
        backstory="Expert analyst with direct api.video access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent api.video 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 api.video. 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 api.video MCP in CrewAI

Yes, you can define agents that use these tools to perform tasks in sequence. It handles the full video stack without human input.

Use the tool_filter option in your agent setup. You can limit which tools each agent can access for better security.

The agents can call `get_video_analytics` to pull performance data. This allows them to report on video reach automatically.

Your video metadata is only accessible via the scoped token you provide. We treat your keys as sensitive and never store them.

Agents can use `delete_video` if you authorize them. We recommend using a moderator agent to confirm deletions before they happen.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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