Tingyun / 听云 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 Tingyun / 听云 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 Tingyun / 听云, 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 Tingyun / 听云 MCP Server
Empower your AI agent to orchestrate your entire digital performance stack with Tingyun (听云), the premier APM and observability platform. By connecting Tingyun to your agent, you transform complex application monitoring, incident response, and performance auditing into a natural conversation. Your agent can instantly list monitored applications, retrieve real-time performance summaries, browse active alerts, and query specific metric data without you ever needing to navigate the Tingyun console. Whether you are troubleshooting a production bottleneck or auditing system health across a distributed architecture, your agent acts as a real-time site reliability assistant, keeping your performance data accurate and your systems responsive.
The Vercel AI SDK gives every Tingyun / 听云 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
- Application Orchestration — List all APM applications and retrieve detailed health and performance summaries.
- Incident Control — Monitor active alerts and browse alert policies to identify and respond to performance issues.
- Infrastructure Auditing — List application instances, external service calls, and database dependencies.
- Metric Querying — Retrieve specific metric data points for applications to analyze trends and anomalies.
- User Experience Insights — Browse Real User Monitoring (RUM) browser applications to audit frontend performance.
The Tingyun / 听云 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 Tingyun / 听云 to Vercel AI SDK via MCP
Follow these steps to integrate the Tingyun / 听云 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 Tingyun / 听云 and passes them to the LLM
Why Use Vercel AI SDK with the Tingyun / 听云 MCP Server
Vercel AI SDK provides unique advantages when paired with Tingyun / 听云 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 Tingyun / 听云 integration everywhere
Built-in streaming UI primitives let you display Tingyun / 听云 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
Tingyun / 听云 + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Tingyun / 听云 MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Tingyun / 听云 in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Tingyun / 听云 tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Tingyun / 听云 capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Tingyun / 听云 through natural language queries
Tingyun / 听云 MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Tingyun / 听云 to Vercel AI SDK via MCP:
get_account_info
Get account metadata
get_app_summary
Get application summary
get_metrics
Query metric data
list_alert_policies
List alert policies
list_alerts
List active alerts
list_app_instances
List application instances
list_applications
List APM applications
list_browser_apps
List RUM browser applications
list_databases
List monitored databases
list_external_services
List external service calls
Example Prompts for Tingyun / 听云 in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Tingyun / 听云 immediately.
"List all applications monitored by Tingyun."
"Show me the performance summary for application ID 12345."
"Check for any critical alerts in Tingyun from today."
Troubleshooting Tingyun / 听云 MCP Server with Vercel AI SDK
Common issues when connecting Tingyun / 听云 to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpTingyun / 听云 + Vercel AI SDK FAQ
Common questions about integrating Tingyun / 听云 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 Tingyun / 听云 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 Tingyun / 听云 to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.