How to Use the Vercel MCP in AutoGen

Q: How do I use Vercel deployment details with Vercel and AutoGen?

Your agents can debate the best course of action using getverceldeploymentinfo. One agent checks the build status, while another assesses if a cleanup is needed by calling deleteverceldeployment.

Q: Can Vercel and AutoGen manage user accounts?

Yes. Agents can use getverceluserprofile to check current user details, ensuring that any actions they take are properly scoped and attributed before proceeding with a change.

Q: What if I need to list all available domains with Vercel and AutoGen?

The listvercelaccountdomains tool provides this data. Your agents can then debate the implications of adding or removing any domain from your account setup.

Q: Does this MCP Server support listing environment variables with Vercel and AutoGen?

The listvercelprojectenvvars tool provides a complete list. Agents use this data to negotiate which variables need to be kept, changed, or deleted.

Run multi-agent debates on Vercel infrastructure using AutoGen.

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Debating Deployment Changes with the MCP Server

Give your agent a task to create a deployment. The `create_vercel_deployment` tool initiates the action, but an opposing agent can immediately call `get_vercel_deployment_info`. They debate whether the initial parameters were correct or if a rollback is safer. The multi-agent system achieves consensus: one agent proposes a change using `delete_vercel_deployment`, and another challenges it by reviewing the current state via listing tools.

Vercel Project Analysis for Consensus

Start by having agents list all projects with `list_vercel_projects`. One agent can then challenge this list, asking for more detail using `get_vercel_project_details` on a specific project. The debate converges on the most accurate and relevant dataset. This forces deliberation over which configuration or set of projects is actually needed to move forward.

Negotiating Environment Variable States

If an agent proposes adding a variable using `add_vercel_environment_variable`, another agent can challenge that by first calling `list_vercel_project_env_vars`. This checks the current state against the proposed change. The debate determines if the new variable is redundant or necessary, making decision-making explicit and traceable.

Setup guide

Set up Vercel 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 Vercel 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="Vercel_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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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="Vercel_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

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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.

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Common questions about Vercel MCP in AutoGen

Your agents can debate the best course of action using `get_vercel_deployment_info`. One agent checks the build status, while another assesses if a cleanup is needed by calling `delete_vercel_deployment`.

Yes. Agents can use `get_vercel_user_profile` to check current user details, ensuring that any actions they take are properly scoped and attributed before proceeding with a change.

The `list_vercel_account_domains` tool provides this data. Your agents can then debate the implications of adding or removing any domain from your account setup.

The `list_vercel_project_env_vars` tool provides a complete list. Agents use this data to negotiate which variables need to be kept, changed, or deleted.

This server handles project metadata, deployment information, account domains, and user profiles. The focus is on system configuration and structure rather than private content.

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