Roboflow MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 29 tools to Add Projects To Folder, Auto Label, Cancel Training, and more
GDPR Free for SubscribersThe Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Roboflow through 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 for Vercel AI SDK
The Roboflow MCP Server for Vercel AI SDK is a standout in the Developer Tools category — giving your AI agent 29 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport { 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 Roboflow, 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 Roboflow MCP Server
Connect Roboflow to your AI agent to streamline your computer vision pipeline. From dataset management to model training and inference, handle your entire CV lifecycle through natural language.
The Vercel AI SDK gives every Roboflow tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 29 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 Management — List projects, create new ones, or fork from Roboflow Universe to jumpstart your development.
- Dataset Operations — Upload images (via URL or Base64), manage versions, and download datasets in various formats like COCO or YOLO.
- Model Training — Start training runs, monitor results, and retrieve precise performance metrics (mAP, precision, recall) for any version.
- Image Search — Search and filter images within your workspace to audit your data and improve model accuracy.
- Inference & Results — Run inference on images and retrieve results to verify model behavior in real-time.
The Roboflow MCP Server exposes 29 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 29 Roboflow tools available for Vercel AI SDK
When Vercel AI SDK connects to Roboflow through Vinkius, your AI agent gets direct access to every tool listed below — spanning computer-vision, dataset-management, model-training, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Add projects to folder on Roboflow
Add projects to a folder (Enterprise)
Auto label on Roboflow
Start an auto-labeling job using foundation models
Cancel training on Roboflow
Cancel an active training job
Create annotation job on Roboflow
Assign a batch of images to a labeler and reviewer
Create folder on Roboflow
Create a project folder (Enterprise)
Create project on Roboflow
Create a new project in a workspace
Delete images on Roboflow
Delete multiple images from a project
Delete project on Roboflow
Delete a project or version (moves to Trash)
Download dataset on Roboflow
Retrieve a download link for a zipped dataset in a specific format
Fork universe project on Roboflow
Fork a public project from Roboflow Universe
Get async task on Roboflow
Track long-running operations like forking or large exports
Get dataset health on Roboflow
Check dataset health (class distribution, missing annotations, etc)
Get image on Roboflow
Get details for a specific image
Get project on Roboflow
Get project details, metadata, and versions
Get root on Roboflow
Verify authentication and retrieve default workspace
Get training results on Roboflow
Retrieve metrics and status for a version training run
Get version on Roboflow
Retrieve metadata for a specific dataset version
List folders on Roboflow
List project folders in a workspace (Enterprise)
List trash on Roboflow
List items in the workspace trash
List workspace projects on Roboflow
List information about a workspace and its projects
Manage image tags on Roboflow
Add, remove, or set tags on an image
Restore trash on Roboflow
Restore an item from the trash
Run inference on Roboflow
Run inference on an image using hosted models
Search project images on Roboflow
Search and filter images within a specific project
Search workspace images on Roboflow
Search and filter images within a workspace
Start training on Roboflow
Start training a model on a dataset version
Stop training on Roboflow
Early stop an active training job
Upload annotation on Roboflow
Attach an annotation file to an existing image
Upload image on Roboflow
Upload an image to a project
Connect Roboflow to Vercel AI SDK via MCP
Follow these steps to wire Roboflow into Vercel AI SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
npm install @ai-sdk/mcp ai @ai-sdk/openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the script
agent.ts and run with npx tsx agent.tsExplore tools
Why Use Vercel AI SDK with the Roboflow MCP Server
Vercel AI SDK provides unique advantages when paired with Roboflow 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 Roboflow integration everywhere
Built-in streaming UI primitives let you display Roboflow 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
Roboflow + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Roboflow MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Roboflow in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Roboflow tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Roboflow capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Roboflow through natural language queries
Example Prompts for Roboflow in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Roboflow immediately.
"List all projects in my Roboflow workspace 'industrial-safety'."
"Upload this image URL to the 'Hard Hat Detection' project in workspace 'industrial-safety'."
"Show me the training metrics for version 5 of the 'Forklift Tracking' project."
Troubleshooting Roboflow MCP Server with Vercel AI SDK
Common issues when connecting Roboflow to Vercel AI SDK through Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpRoboflow + Vercel AI SDK FAQ
Common questions about integrating Roboflow 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.Explore More MCP Servers
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