How to Use the Videco MCP in AutoGen

Q: Can I list videos using Videco with AutoGen?

Yes. You'll give one agent the tool set including listvideos. That agent pulls the asset list, and then another agent might call getvideo to get the specific details for review.

Build consensus-driven marketing decisions with Videco using AutoGen.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Videco MCP to AutoGen

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

GDPR Free for Subscribers

Setup Videco with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Debate Campaign Strategy via MCP Server

You can set up multiple agents—say, a 'Marketing Agent' and an 'Analytics Agent.' The Marketing Agent calls `list_campaigns` to see what exists. The Analytics Agent then challenges that list by calling `get_video_analytics`, forcing the system to debate the best next steps.

Consensus on Video Creation with Videco

Need to decide if a video should be created? One agent can check connectivity using `check_videco_status`. Another agent might call `get_lead` to verify the target audience. They debate whether enough data exists before finally deciding to run `create_video`.

Systematic Lead Qualification Flow

Agents can simulate a full qualification process. A 'Data Agent' calls `list_leads`, and the 'Review Agent' then uses that list to call `get_lead` for individual deep dives. This negotiation ensures all criteria are met before any action is taken.

Setup guide

Set up Videco MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Videco tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Videco_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Videco data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Videco_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Videco data")
    print(result.messages[-1].content)

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 Videco. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Videco now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Videco MCP in AutoGen

You can assign different agents specific tools from the MCP Server, like `get_campaign` or `list_campaigns`. The agents then talk through the process, ensuring that multiple data points are checked before a conclusion is reached.

AutoGen allows you to make several agents responsible for different aspects. One agent can collect `get_video_analytics` data, while another reviews that metric against the campaign goals provided by `get_campaign`.

Yes. You'll give one agent the tool set including `list_videos`. That agent pulls the asset list, and then another agent might call `get_video` to get the specific details for review.

It's perfect. Since AutoGen models deliberation, it handles scenarios where simply calling a tool isn't enough—it forces your agents to discuss the results of `get_lead` before proceeding.

This server touches lead details. The primary PII you interact with is stored in the lead records, accessible via the `get_lead` tool call.

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