Smithery MCP Server for Vercel AI SDK 11 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Smithery 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 Smithery, 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 Smithery MCP Server
What you can do
Connect AI agents to the Smithery Registry for comprehensive MCP server discovery and management:
The Vercel AI SDK gives every Smithery tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 11 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.
- Search MCP servers — find servers by name, description, or tags with semantic search
- Get server details — review metadata, verification status, and user counts
- Discover tools — list all tools (functions) exposed by any registered MCP server
- Discover resources — list all data resources available from MCP servers
- Discover prompts — list all prompt templates exposed by MCP servers
- Create connections — connect to MCP servers via Smithery Connect with automatic OAuth handling
- Manage connections — list, inspect, and remove MCP server connections
- Generate service tokens — create scoped, time-limited tokens for frontend/agent access
- View analytics — monitor server usage, adoption trends, and performance metrics
The Smithery MCP Server exposes 11 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 Smithery to Vercel AI SDK via MCP
Follow these steps to integrate the Smithery 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 11 tools from Smithery and passes them to the LLM
Why Use Vercel AI SDK with the Smithery MCP Server
Vercel AI SDK provides unique advantages when paired with Smithery 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 Smithery integration everywhere
Built-in streaming UI primitives let you display Smithery 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
Smithery + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Smithery MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Smithery in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Smithery tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Smithery capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Smithery through natural language queries
Smithery MCP Tools for Vercel AI SDK (11)
These 11 tools become available when you connect Smithery to Vercel AI SDK via MCP:
create_connection
Smithery handles OAuth, tokens, and sessions automatically. Requires the server namespace and connection configuration (mcpUrl, optional headers, metadata). Returns the connection ID, status, and server info. Use this to integrate MCP servers into your applications without managing authentication complexity. Create a new connection to an MCP server via Smithery Connect
create_service_token
The token has limited permissions defined by the policy (namespaces, resources, operations, metadata, TTL). Returns the token string. Use this to provide secure, time-limited access to MCP servers without exposing your main API key. Generate a scoped service token for frontend/agent access to MCP servers
delete_connection
This action cannot be undone. Requires namespace and connection ID. Use this to clean up unused connections or revoke access. Remove an MCP server connection
get_connection
Requires namespace and connection ID. Use this to review connection details or troubleshoot connectivity issues. Get detailed information about a specific MCP connection
get_server_analytics
Requires the server qualified name. Use this to monitor server adoption, identify usage trends, or troubleshoot performance issues. Get usage analytics for a specific MCP server
get_server_details
Requires the qualified name (e.g., "smithery/hello-world" or "github/github") from search_servers results. Use this to review server capabilities before connecting. Get detailed information about a specific MCP server from the Smithery registry
get_server_prompts
Returns prompt names, descriptions, and argument definitions. Requires the server qualified name. Use this to discover reusable prompt workflows available from the server. List all prompt templates exposed by a specific MCP server
get_server_resources
Returns resource URIs, names, descriptions, and MIME types. Requires the server qualified name. Use this to understand what data the server provides read access to. List all resources exposed by a specific MCP server
get_server_tools
Returns tool names, descriptions, input schemas, and annotations. Requires the server qualified name. Use this to understand what actions the server can perform before connecting it to your agents. List all tools exposed by a specific MCP server
list_connections
Returns connection IDs, names, statuses, creation dates, and metadata. Use this to audit which connections are active, review connection configurations, or identify unused connections. List all connections for a specific MCP server namespace
search_servers
Returns matching servers with qualified names, descriptions, verification status, user counts, and deployment info. Use optional filters to narrow by namespace, verified status, or deployment state. Results include pagination metadata. Use this as the first step to discover available MCP servers before connecting or installing them. Search the Smithery registry for MCP servers by name, description, or tags
Example Prompts for Smithery in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Smithery immediately.
"Search for verified GitHub-related MCP servers"
"Show me all tools exposed by the Stripe MCP server"
"Create a connection to the Slack MCP server for my workspace"
Troubleshooting Smithery MCP Server with Vercel AI SDK
Common issues when connecting Smithery to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpSmithery + Vercel AI SDK FAQ
Common questions about integrating Smithery 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 Smithery 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 Smithery to Vercel AI SDK
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.