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How to Use the Vercel MCP in Pydantic AI

Control Vercel deployments and infrastructure with Pydantic AI for type safety.

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Connect Vercel MCP to Pydantic AI

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

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Manage projects lifecycle

The `list_projects` tool shows all existing Vercel projects in the account. If you need to add one, use `create_project`, passing both a name and a framework slug. Need to wipe a project? Use `delete_project`. Just remember that action is irreversible.

Check build status and aliases

`list_deployments` lists recent CI/CD builds for any given project. You can also view the specific routing mappings using `list_project_aliases`. Pulling detailed configuration data is straightforward with `get_project_details`.

Control live deployments

To kick off a build, use `trigger_github_deployment`, providing the necessary project name and Git ref. This forces Vercel to start compiling. If you need to stop an ongoing process, call `cancel_active_build`.

Setup guide

Set up Vercel MCP in Pydantic AI

Prerequisites

  • Python 3.10+ installed
  • pydantic-ai-slim[fastmcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install Pydantic AI with FastMCP

    Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.

  2. 2

    Configure the FastMCPToolset

    Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.

  3. 3

    Create and run your agent

    Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py
from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "vercel-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Vercel tools.",
)

result = await agent.run("List recent Vercel transactions")
print(result.output)

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Common questions about Vercel MCP in Pydantic AI

The agent uses the MCP Server's `list_projects` tool. It retrieves a complete listing of every project configured in your account.
You can use `trigger_github_deployment`. You just have to tell the server the project name and the specific Git reference you want to compile.
Use `list_account_domains` for an overview of all apex domains managed by Vercel. For subdomains, check `list_project_aliases`.
Use the `get_deployment_details` tool to pull deep information about a specific run. You can also use `list_deployments` for recent builds.
This server touches high-level apex domain records via `list_account_domains`, and it manages project-specific subdomain routing mappings through `list_project_aliases`.

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