Strapi MCP Server for Vercel AI SDK 9 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Strapi through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
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 Strapi, 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 Strapi MCP Server
Integrate the robust headless architecture of Strapi seamlessly into your conversational LLM workflows. By linking your AI securely to the Strapi REST ecosystem, engineering and content teams can effortlessly design schema types, interact with entries, and orchestrate media libraries directly from the terminal.
The Vercel AI SDK gives every Strapi tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 9 tools through the 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
- Architecture Discovery — Quickly evaluate top-level content structures invoking
list_content_typesand systematically paginate underlying rows executinglist_entries. - Content Construction — Drive agile content updates creating new JSON-formatted parameters natively by calling
create_entryor updating existing rows viaupdate_entry. - Asset Orchestration — Monitor uploaded visual data traversing the Media Library securely with
list_assetsor uploading remote dependencies instantly usingupload_media_asset. - Audit & Clearance — Protect production integrity by securely tracking and listing authorized active members leveraging
list_cms_users.
The Strapi MCP Server exposes 9 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 Strapi to Vercel AI SDK via MCP
Follow these steps to integrate the Strapi 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 9 tools from Strapi and passes them to the LLM
Why Use Vercel AI SDK with the Strapi MCP Server
Vercel AI SDK provides unique advantages when paired with Strapi 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 Strapi integration everywhere
Built-in streaming UI primitives let you display Strapi 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
Strapi + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Strapi MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Strapi in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Strapi tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Strapi capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Strapi through natural language queries
Strapi MCP Tools for Vercel AI SDK (9)
These 9 tools become available when you connect Strapi to Vercel AI SDK via MCP:
create_entry
Provide the plural ID and a JSON string of fields. Creates a new entry for a specific content type
delete_entry
This action is irreversible. Permanently deletes a content entry
get_entry_details
Retrieves details for a specific content entry
list_assets
Lists media assets stored in the Strapi Media Library
list_cms_users
Lists all registered CMS users
list_content_types
Lists all content types (collections and single types) defined in Strapi
list_entries
Provide the plural ID of the content type (e.g., "articles"). Lists entries for a specific content type
update_entry
Provide the plural ID, entry ID, and field updates. Updates fields of an existing content entry
upload_media_asset
Provide the public file URL to be fetched and uploaded. Uploads a new file to the Media Library
Example Prompts for Strapi in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Strapi immediately.
"Review my Strapi content types and show the schema for 'product'."
"Construct a newly formatted post about system updates in the 'articles' content type."
"Upload a new promotional image dependency securely into the Media Library."
Troubleshooting Strapi MCP Server with Vercel AI SDK
Common issues when connecting Strapi to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpStrapi + Vercel AI SDK FAQ
Common questions about integrating Strapi 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 Strapi 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 Strapi to Vercel AI SDK
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.