How to integrate Vercel MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Vercel to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Vercel agent that can deploy latest changes to my project, add api key as production environment variable, check if mydomain.com is available for purchase, delete failed deployment by id through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Vercel account through Composio's Vercel MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Vercel
  • Configure an AI agent that can use Vercel as a tool
  • Run a live chat session where you can ask the agent to perform Vercel operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the Vercel MCP server, and what's possible with it?

The Vercel MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Vercel account. It provides structured and secure access to your Vercel projects and deployments, so your agent can perform actions like creating deployments, managing environment variables, handling edge configs, and checking domain statuses on your behalf.

  • Automated deployments and rollbacks: Easily instruct your agent to create new deployments or remove outdated ones, streamlining your release process without manual steps.
  • Environment variable management: Let your agent add or update sensitive configuration values across different environments, ensuring your projects are set up correctly before a deploy.
  • Edge configuration and token handling: Have your agent create new edge configs or generate secure tokens for read-only access, optimizing how your content is served globally.
  • Domain availability and pricing checks: Ask your agent to verify if a domain is available and fetch the latest price before you make a purchase decision.
  • Authentication token management: Enable your agent to create or revoke Vercel API tokens, giving you fine-grained control over programmatic access to your account.

Supported Tools & Triggers

Tools
Add Environment VariableTool to add an environment variable to a vercel project.
Check Cache Artifact ExistsTool to check if a cache artifact exists by its hash.
Check Domain AvailabilityTool to check if a domain is available for registration.
Check Domain PriceTool to check the price for a domain before purchase.
Create Auth TokenTool to create a new authentication token.
Create Edge ConfigTool to create a new edge config for a vercel project.
Create Edge Config TokenTool to create a new token for a specific edge config.
Create new deploymentTool to create a new deployment.
Delete Auth TokenTool to delete an authentication token.
Delete DeploymentTool to delete a specific deployment by its unique id.
Delete Edge Config TokensTool to delete tokens associated with a specific edge config.
Delete Environment VariableTool to delete a specific environment variable from a project.
Delete Vercel ProjectTool to delete a specific project by its id or name.
Deploy Edge FunctionDeploy edge functions to vercel.
Get Auth Token MetadataTool to retrieve metadata for an authentication token.
Get deployment detailsTool to retrieve detailed information about a specific deployment.
Get Deployment EventsTool to retrieve events related to a specific deployment.
Get Deployment LogsTool to retrieve logs for a specific vercel deployment.
Get Domain Transfer InfoTool to get information required to transfer a domain to vercel.
Get Edge ConfigTool to retrieve details of a specific edge config.
Get Edge Config ItemTool to retrieve a specific item within an edge config.
Get Edge Config TokenTool to retrieve details of a specific token associated with an edge config.
Get Vercel ProjectTool to retrieve information about a vercel project by id or name.
List Vercel AliasesTool to list all aliases for the authenticated user or team.
List All DeploymentsTool to list all deployments.
List Auth TokensTool to list authentication tokens.
List Deployment ChecksTool to retrieve a list of checks for a specific deployment.
List Edge Config ItemsTool to retrieve a list of items within a specific edge config.
List Edge ConfigsTool to list all edge configs.
List Edge Config TokensTool to retrieve a list of tokens for a specific edge config.
List Environment VariablesTool to list environment variables for a specific project.
List All TeamsTool to list all teams accessible to the authenticated user.
Update Edge ConfigTool to update an existing edge config.
Update Edge Config ItemsTool to update items within a specific edge config.
Update Vercel ProjectTool to update an existing project.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Vercel project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Vercel.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Vercel Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["vercel"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only vercel.
  • The router checks the user's Vercel connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Vercel.
  • This approach keeps things lightweight and lets the agent request Vercel tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Vercel. "
        "Help users perform Vercel operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Vercel and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Vercel operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Vercel.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Vercel and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["vercel"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Vercel. "
        "Help users perform Vercel operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Vercel MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Vercel.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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Vercel AI SDK

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Mastra AI

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LlamaIndex

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CrewAI

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Use Vercel MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Vercel MCP?

With a standalone Vercel MCP server, the agents and LLMs can only access a fixed set of Vercel tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Vercel and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Vercel tools.

Can I manage the permissions and scopes for Vercel while using Tool Router?

Yes, absolutely. You can configure which Vercel scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Vercel data and credentials are handled as safely as possible.

Used by agents from

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