Bring Sandboxes
to Vercel AI SDK
Learn how to connect Daytona (Dev Workspaces) to Vercel AI SDK and start using 28 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 Daytona (Dev Workspaces) MCP Server?
Connect your Daytona account to any AI agent to orchestrate cloud-based development environments through natural language. Daytona provides standardized, ephemeral sandboxes that can be provisioned and managed on demand.
What you can do
- Sandbox Orchestration — List, create, start, stop, and delete sandboxes with specific CPU, memory, and disk configurations.
- Snapshot Management — Create and manage snapshots to preserve environment states or activate them for new sandboxes using
create_snapshotandactivate_snapshot. - API Key Control — Manage your authentication keys directly, including listing and creating new access tokens via
list_api_keysandcreate_api_key. - Resource Scaling — Dynamically resize sandbox resources (vCPU, RAM, Disk) to match your workload requirements using
resize_sandbox. - Volume & Storage — Inspect and manage persistent volumes and snapshots for your dev environments.
How it works
- Subscribe to this server
- Enter your Daytona API Key
- Start managing your dev infrastructure from Claude, Cursor, or any MCP client
Who is this for?
- DevOps Engineers — Automate the lifecycle of test environments and sandboxes.
- Software Developers — Spin up fresh coding environments without leaving the chat or IDE.
- QA Teams — Quickly recover sandboxes from error states or fork existing environments for debugging.
Built-in capabilities (28)
Activate a snapshot
Archive a sandbox
Create a new Daytona API key
Create a new Daytona sandbox
Create a new snapshot
Create a new volume
Deactivate a snapshot
Delete an API key by name
Delete a sandbox
Delete a snapshot
Delete a volume
Fork an existing sandbox
Get details of a specific API key by name
Get details of the currently authenticated API key
Get details of a specific sandbox
Get a signed preview URL for a specific port on a sandbox
Get details of a specific snapshot
Get details of a specific volume by ID
Get details of a specific volume by name
List Daytona API keys
List all Daytona sandboxes
List all Daytona sandboxes (paginated)
List all Daytona snapshots
List all Daytona volumes
Recover a sandbox from an error state
Resize sandbox resources
Start a stopped sandbox
Stop a running sandbox
Why Vercel AI SDK?
The Vercel AI SDK gives every Daytona (Dev Workspaces) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 28 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
- —
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 Daytona (Dev Workspaces) integration everywhere
- —
Built-in streaming UI primitives let you display Daytona (Dev Workspaces) 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
Daytona (Dev Workspaces) in Vercel AI SDK
Daytona (Dev Workspaces) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Daytona (Dev Workspaces) 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 Daytona (Dev Workspaces) in Vercel AI SDK
The Daytona (Dev Workspaces) 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 28 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
Daytona (Dev Workspaces) for Vercel AI SDK
Every tool call from Vercel AI SDK to the Daytona (Dev Workspaces) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I change the resources of an existing sandbox?
Yes, you can use the resize_sandbox tool to update the CPU, memory, or disk size of a specific sandbox by providing its ID or name.
How do I create a new environment with a specific Docker image?
Use the create_sandbox tool and provide the image parameter with the desired Docker or OCI image name.
What should I do if a sandbox is in an error state?
You can use the recover_sandbox tool to attempt to restore a sandbox from an error state back to a functional one.
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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