How to Use the WebVizio MCP in OpenAI Agents SDK
Build production web feedback pipelines with the OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect WebVizio MCP to OpenAI Agents SDK
Create your Vinkius account to connect WebVizio to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Manage WebVizio Projects with the MCP Server
You can create a new project using `create_webvizio_project`, which sets up a dedicated space for feedback. Then, you'll get an overview of all existing workstreams by calling `list_webvizio_projects`. Need to check what’s already set up? Use `get_webvizio_project_details` to pull specific information on any project ID.
Handle Task Updates with the OpenAI Agents SDK
The agent handles task lifecycle management. You can create a new feedback item via `create_webvizio_task`, and later change its status or details using `update_webvizio_task`. Check on existing work items anytime; `get_webvizio_task_details` gives you the full context for any specific task.
Gather Detailed Web Feedback
When a team member finds an issue, they leave comments. Your agent can list these comments using `list_webvizio_comments`, or add new ones directly with `add_webvizio_comment`. Also useful is checking out the project roster by running `list_webvizio_tasks`, which gives you a full view of all tasks tied to that project.
Set up WebVizio MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all WebVizio tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives WebVizio tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate WebVizio tools and returns structured results. Copy the full example on the right to get started.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse
async def main():
async with MCPServerSse(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as server:
agent = Agent(
name="WebVizio Agent",
instructions="You have access to WebVizio tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by WebVizio. 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 WebVizio MCP in OpenAI Agents SDK
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