Stoplight MCP Server for Vercel AI SDK 7 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Stoplight through the 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 Stoplight, 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 Stoplight MCP Server
Integrate the industry-leading API design and documentation capabilities of Stoplight into your conversational AI workflows. Empower your engineering teams to explore workspaces, evaluate OpenAPI schemas, and audit API projects natively from their conversational assistant. Securely map your AI to your Stoplight workspace, enabling the orchestration of complex documentation tasks, project navigation, and architectural reviews naturally without switching contexts or opening complex dashboards.
The Vercel AI SDK gives every Stoplight tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 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.
What you can do
- Workspace Exploration — Rapidly inspect top-level organizational containers invoking
list_workspaces, and track operational changes programmatically leveraginglist_workspace_activity. - Project Management — Audit your API documentation repositories cataloging initiatives securely using
list_projects, and retrieve full visibility metadata invokingget_project_details. - Schema & Documentation Discovery — Dive deeply into specific documentation structures retrieving files, endpoints, and models leveraging
list_project_nodes, and parse their raw text safely utilizingget_node_details. - Team & Governance — Map project ownership accurately and enforce governance metrics iteratively assigning roles retrieving authorized contributors naturally via
list_workspace_members.
The Stoplight MCP Server exposes 7 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 Stoplight to Vercel AI SDK via MCP
Follow these steps to integrate the Stoplight 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 7 tools from Stoplight and passes them to the LLM
Why Use Vercel AI SDK with the Stoplight MCP Server
Vercel AI SDK provides unique advantages when paired with Stoplight 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 Stoplight integration everywhere
Built-in streaming UI primitives let you display Stoplight 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
Stoplight + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Stoplight MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Stoplight in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Stoplight tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Stoplight capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Stoplight through natural language queries
Stoplight MCP Tools for Vercel AI SDK (7)
These 7 tools become available when you connect Stoplight to Vercel AI SDK via MCP:
get_node_details
Retrieves details for a specific documentation node
get_project_details
Retrieves details for a specific Stoplight project
list_project_nodes
Lists all documentation nodes (files, endpoints, models) within a project
list_projects
Lists all projects in a specific Stoplight workspace
list_workspace_activity
Lists recent activity logs for a Stoplight workspace
list_workspace_members
Lists all members of a Stoplight workspace
list_workspaces
Lists all accessible Stoplight workspaces
Example Prompts for Stoplight in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Stoplight immediately.
"List my Stoplight projects and show recent workspace activity."
"Retrieve the detailed schema documentation for the processing node in our core billing API project."
"List all active members in the current workspace."
Troubleshooting Stoplight MCP Server with Vercel AI SDK
Common issues when connecting Stoplight to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpStoplight + Vercel AI SDK FAQ
Common questions about integrating Stoplight 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 Stoplight 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 Stoplight to Vercel AI SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.