Frontify 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 Frontify 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 Frontify, 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 Frontify MCP Server
Connect your Frontify account to any AI agent and take full control of your digital asset management (DAM), brand guidelines, and collaborative workspaces through natural conversation.
The Vercel AI SDK gives every Frontify 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
- Workspace Project Orchestration — Enumerate explicitly registered project schemas and gather required IDs to browse and discover collaborative workspaces natively
- Asset Lifecycle Management — Retrieve detailed metadata for project assets and perform structural extraction of properties driving active media limits flawslessly
- Brand Guideline Discovery — Identify precise active arrays spanning rented documentation trees, identifying where strict UI/UX constraints and brand rules are registered
- Metadata Mutation — Update global asset boundaries by substituting attributes like titles and descriptions securely through GraphQL mutation logic
- Media Content Oversight — Analyze specific global boundaries iterating through brands to discover exact tenant separations inside a single account
- Identity & User Management — Retrieve the exact structural matching verifying identity schemas and invite new users directly into designated project workspaces securely
- Digital Asset Purging — Irreversibly vaporize explicit app nodes to remove media assets and separating limits pulling items offline flawlessly
- Custom GraphQL Execution — Identify bounded routing spaces inside the headless Frontify DAM utilizing native GraphQL strings for advanced structural queries
The Frontify 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 Frontify to Vercel AI SDK via MCP
Follow these steps to integrate the Frontify 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 Frontify and passes them to the LLM
Why Use Vercel AI SDK with the Frontify MCP Server
Vercel AI SDK provides unique advantages when paired with Frontify 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 Frontify integration everywhere
Built-in streaming UI primitives let you display Frontify 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
Frontify + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Frontify MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Frontify in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Frontify tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Frontify capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Frontify through natural language queries
Frontify MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Frontify to Vercel AI SDK via MCP:
execute_graphql_payload
Identify bounded routing spaces inside the Headless Frontify DAM utilizing native GraphQL strings
get_account_limits
Inspect deep internal arrays mitigating specific Picture constraints
get_project_assets
Retrieve explicit Cloud logging tracing explicit Asset Limits
invite_workspace_user
Dispatch an automated validation check routing explicit Workspace roles
list_brand_guidelines
Identify precise active arrays spanning rented Documentation trees
list_native_brands
Perform structural extraction of properties driving active Global namespaces
list_platform_users
Retrieve the exact structural matching verifying Identity schemas
list_workspace_projects
Enumerate explicitly attached structured rules exporting active Workspaces
patch_asset_metadata
Mutate global Web CRM boundaries substituting Attributes safely
wipe_media_asset
Irreversibly vaporize explicit App nodes dropping live Database bytes
Example Prompts for Frontify in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Frontify immediately.
"List all projects in my Frontify workspace"
"Show me the brand guidelines for 'Acme Corp'"
"Invite 'designer@example.com' to project 'abc-123'"
Troubleshooting Frontify MCP Server with Vercel AI SDK
Common issues when connecting Frontify to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpFrontify + Vercel AI SDK FAQ
Common questions about integrating Frontify 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 Frontify 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 Frontify to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.