How to Use the Vercel MCP in OpenAI Agents SDK
Finish production agents fast. OpenAI Agents SDK makes Vercel deployments actionable.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Vercel MCP to OpenAI Agents SDK
Create your Vinkius account to connect Vercel 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 Vercel Deployments with the MCP Server
Use `create_vercel_deployment` to fire up a new version of your app instantly. You can also use `delete_vercel_deployment` if you need to take down an old build. It’s simple; just tell it which deployment ID to target.
Check Vercel Project Status using the MCP Server
Need to know what a project is doing? `get_vercel_project_details` fetches all the necessary info on a specific project. Plus, you can check out environment settings by listing variables with `list_vercel_project_env_vars`.
Handle Vercel Accounts and Teams via MCP Server
The server lets your agent see what accounts are available through `list_vercel_account_domains`. You can also scope down to specific teams using `list_vercel_teams` or list all projects across an account with `list_vercel_projects`. This keeps things organized.
Set up Vercel 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 Vercel tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Vercel tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Vercel 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="Vercel Agent",
instructions="You have access to Vercel 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 Vercel. 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.
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 Vercel MCP in OpenAI Agents SDK
Use it with your favorite AI tools
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