Porter PaaS MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Porter PaaS through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Porter PaaS, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Porter PaaS MCP Server
Connect your Porter account to any AI agent and take full programmatic control over your Kubernetes infrastructure natively.
The Vercel AI SDK gives every Porter PaaS tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Projects & Clusters — List high-level organizational bounds, EKS/GKE clusters, and deployment zones
- Applications & Environments — Map staging/production namespaces, check active web services, and resolve container requirements
- Operations — Restart app pods gracefully or forcefully deploy specific image tags when resolving CI/CD breaks
- Helm Inspections — Check low-level Helm charts behind active components (like Postgres or Redis)
The Porter PaaS MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Porter PaaS to Vercel AI SDK via MCP
Follow these steps to integrate the Porter PaaS MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from Porter PaaS and passes them to the LLM
Why Use Vercel AI SDK with the Porter PaaS MCP Server
Vercel AI SDK provides unique advantages when paired with Porter PaaS through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Porter PaaS integration everywhere
Built-in streaming UI primitives let you display Porter PaaS tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Porter PaaS + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Porter PaaS MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Porter PaaS in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Porter PaaS tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Porter PaaS capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Porter PaaS through natural language queries
Porter PaaS MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Porter PaaS to Vercel AI SDK via MCP:
deploy_app_tag
Assigns a raw docker registry digest/tag directly causing Kubernetes to perform an absolute image pull orchestrating a fresh deployment state spanning replica boundaries. Forcefully mutate the executed Docker image running internally
get_app
Includes explicit CPU metrics requested, RAM limits mapped locally to the JVM/Node instances, and internal registry image hashes resolving at runtime. Analyze architectural bindings orchestrating a specific App
get_cluster
Inspect deep cloud credentials generating a specific K8s Cluster
get_project
Perform structural extraction of metadata linked to a Porter Project
list_apps
Discovers precisely which App routing identities expose `porter.run` subdomains or linked target custom apex mappings. Inventory deployed discrete Applications mapping to a Cluster
list_clusters
Exposes crucial execution zones hosting absolute memory nodes. List underlying target cloud Kubernetes definitions bounds to Porter
list_environments
Extract logic isolation environments overlapping the Cluster
list_helm_releases
Vital for verifying if dependent third-party apps (e.g. Postgres databases or Metabase) deployed aside the primary stack succeeded during installation phases. List underlying operational Helm configurations inside a namespace
list_projects
Fetches indispensable integer `projectId` arrays coordinating everything strictly downstream inside AWS/GCP clusters. Identify base Porter PaaS organizational scopes
restart_app
Mandatory during severe connection leakage scenarios impacting native processes without modifying the fundamental code layer deployment tag. Instruct the Kubernetes API to bounce the App deployment replicas
Example Prompts for Porter PaaS in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Porter PaaS immediately.
"List all applications currently running in cluster ID 5 on the Production environment."
"The queue worker is completely hung. Please perform a forceful restart of the `async-worker` app."
"We just built a hotfix on main. Deploy the image tag `d83a1b1` strictly onto `portal-frontend`."
Troubleshooting Porter PaaS MCP Server with Vercel AI SDK
Common issues when connecting Porter PaaS to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpPorter PaaS + Vercel AI SDK FAQ
Common questions about integrating Porter PaaS MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Porter PaaS with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Porter PaaS to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.