Bring Cloud Computing
to Vercel AI SDK
Learn how to connect Scaleway to Vercel AI SDK and start using 3 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Scaleway MCP Server?
Connect your Scaleway account to any AI agent to manage your cloud infrastructure through natural language. This server provides direct access to the Scaleway Instances API.
What you can do
- Instance Discovery — List all virtual machines across different availability zones (e.g., fr-par-1, nl-ams-1)
- Provisioning — Create new instances by specifying names, commercial types (like DEV1-S), and image IDs
- Power Management — Remotely power on, power off, or reboot your servers
- Lifecycle Control — Terminate instances that are no longer needed directly from the chat
How it works
- Subscribe to this server
- Enter your Scaleway Secret Key
- Start managing your cloud resources from Claude, Cursor, or any MCP-compatible client
Who is this for?
- DevOps Engineers — quickly check server status or reboot instances without leaving the terminal or IDE
- Developers — spin up new development environments using simple text commands
- Cloud Architects — audit active resources across multiple zones efficiently
Built-in capabilities (3)
Create a new Scaleway instance (server)
List Scaleway instances (servers) in a specific zone
Perform an action on a Scaleway instance (e.g., poweron, poweroff)
Why Vercel AI SDK?
The Vercel AI SDK gives every Scaleway tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 3 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
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TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
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Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Scaleway integration everywhere
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Built-in streaming UI primitives let you display Scaleway tool results progressively in React, Svelte, or Vue components
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Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Scaleway in Vercel AI SDK
Scaleway and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Scaleway to Vercel AI SDK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Scaleway in Vercel AI SDK
The Scaleway 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. All 3 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Vercel AI SDK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Scaleway for Vercel AI SDK
Every tool call from Vercel AI SDK to the Scaleway MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I see my servers in a specific region like Paris?
Use the list_instances tool and provide the zone parameter (e.g., 'fr-par-1'). The agent will return a list of all instances currently provisioned in that specific Scaleway zone.
Can I reboot or shut down a server using this integration?
Yes! The perform_instance_action tool allows you to send 'poweron', 'poweroff', 'reboot', or 'terminate' commands to any specific server ID within a zone.
What information is needed to create a new instance?
To use create_instance, you need to provide the zone, a name for the server, the commercial type (e.g., 'DEV1-S'), and the image ID or label you wish to deploy.
How does the Vercel AI SDK connect to MCP servers?
Import 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?
Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
Does it support streaming tool results?
Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.
createMCPClient is not a function
Install: npm install @ai-sdk/mcp
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