SwaggerHub MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect SwaggerHub through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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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 SwaggerHub, 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 SwaggerHub MCP Server
Integrate SwaggerHub, the enterprise platform for API design and documentation, directly into your conversational workflows with the intelligent MCP connector. Transform your LLM into an active technical architect, empowering it to securely index, validate, and retrieve full OpenAPI specifications directly from your organizational directories. Eradicate context-switching by verifying CI/CD integration pipelines, scanning centralized API definitions, and pulling structural component domains intuitively without having to hunt through graphical interfaces.
The Vercel AI SDK gives every SwaggerHub tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 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
- API Cataloging & Specs — Query an entire organizational API roster using
list_apisand pull exact OpenAPI JSON configurations cleanly callingget_api_version_spec. - Component Reusability Insights — Investigate generic shared definitions executing
list_domainsand fetch core parameters seamlessly viaget_domain_details. - Project & Lifecycle Control — Map team infrastructures inspecting groupings natively with
list_projectsand verify operational logic by callingget_project_details. - Ecosystem Verification — Audit backend dependencies natively invoking
list_api_integrationsto test GitHub, AWS, and GitLab sync parameters tied to your specs.
The SwaggerHub MCP Server exposes 10 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 SwaggerHub to Vercel AI SDK via MCP
Follow these steps to integrate the SwaggerHub 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 10 tools from SwaggerHub and passes them to the LLM
Why Use Vercel AI SDK with the SwaggerHub MCP Server
Vercel AI SDK provides unique advantages when paired with SwaggerHub 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 SwaggerHub integration everywhere
Built-in streaming UI primitives let you display SwaggerHub 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
SwaggerHub + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the SwaggerHub MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query SwaggerHub in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate SwaggerHub tools and return structured JSON responses to any frontend
Chatbots with tool use: embed SwaggerHub capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with SwaggerHub through natural language queries
SwaggerHub MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect SwaggerHub to Vercel AI SDK via MCP:
get_api_details
Retrieves metadata for a SwaggerHub API definition
get_api_version_spec
Retrieves a specific version of a SwaggerHub API definition (OpenAPI spec)
get_domain_details
Retrieves metadata for a SwaggerHub domain
get_project_details
Retrieves details of a SwaggerHub project
list_api_integrations
Lists all CI/CD integrations configured for a SwaggerHub API
list_api_templates
Lists all available API templates on SwaggerHub
list_apis
List all API definitions owned by a SwaggerHub user or organization
list_domains
Lists all shared domains (reusable components) owned by a user or org
list_projects
Lists all projects in a SwaggerHub organization
search_apis
Search all public APIs on SwaggerHub by keyword
Example Prompts for SwaggerHub in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with SwaggerHub immediately.
"Search for public API specifications related to 'payment gateway' on SwaggerHub."
"List all active projects in our SwaggerHub organization."
"Ensure that the 'Acme-Billing' API has AWS API Gateway integration synced currently."
Troubleshooting SwaggerHub MCP Server with Vercel AI SDK
Common issues when connecting SwaggerHub to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpSwaggerHub + Vercel AI SDK FAQ
Common questions about integrating SwaggerHub 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 SwaggerHub 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 SwaggerHub to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.