Guance Cloud / 观测云 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 Guance Cloud / 观测云 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 Guance Cloud / 观测云, 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 Guance Cloud / 观测云 MCP Server
Empower your AI agent to orchestrate your entire observability stack with Guance Cloud (观测云), the leading next-generation monitoring platform. By connecting Guance Cloud to your agent, you transform complex system monitoring, log analysis, and incident response into a natural conversation. Your agent can instantly list your monitors, retrieve detailed dashboard configurations, browse system events, and even execute Data Query Language (DQL) statements without you ever needing to navigate the Guance console. Whether you are troubleshooting a production outage or auditing resource usage, your agent acts as a real-time site reliability assistant, keeping your infrastructure data accurate and your systems healthy.
The Vercel AI SDK gives every Guance Cloud / 观测云 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
- Workspace Orchestration — Retrieve detailed metadata and status information for your Guance Cloud workspace.
- Monitoring Control — List and retrieve detailed configurations for all system monitors and alert rules.
- Event Auditing — Browse real-time observability events, including alerts, errors, and system changes.
- Data Querying — Execute powerful DQL statements to retrieve specific metrics and logging data via natural language.
- Operations Insights — Monitor billing usage and manage API access keys for your organizational infrastructure.
The Guance Cloud / 观测云 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 Guance Cloud / 观测云 to Vercel AI SDK via MCP
Follow these steps to integrate the Guance Cloud / 观测云 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 Guance Cloud / 观测云 and passes them to the LLM
Why Use Vercel AI SDK with the Guance Cloud / 观测云 MCP Server
Vercel AI SDK provides unique advantages when paired with Guance Cloud / 观测云 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 Guance Cloud / 观测云 integration everywhere
Built-in streaming UI primitives let you display Guance Cloud / 观测云 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
Guance Cloud / 观测云 + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Guance Cloud / 观测云 MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Guance Cloud / 观测云 in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Guance Cloud / 观测云 tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Guance Cloud / 观测云 capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Guance Cloud / 观测云 through natural language queries
Guance Cloud / 观测云 MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Guance Cloud / 观测云 to Vercel AI SDK via MCP:
get_billing
Get billing usage
get_event
Get event details
get_monitor
Get monitor details
get_workspace
Get workspace information
list_access_keys
List workspace access keys
list_dashboards
List all dashboards
list_events
) from the workspace. List observability events
list_log_sources
List log data sources
list_monitors
List all monitors
query_data
Query Guance data (DQL)
Example Prompts for Guance Cloud / 观测云 in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Guance Cloud / 观测云 immediately.
"List all active monitors in Guance Cloud."
"Show me recent events from the last hour."
"Query average CPU usage using DQL."
Troubleshooting Guance Cloud / 观测云 MCP Server with Vercel AI SDK
Common issues when connecting Guance Cloud / 观测云 to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpGuance Cloud / 观测云 + Vercel AI SDK FAQ
Common questions about integrating Guance Cloud / 观测云 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 Guance Cloud / 观测云 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 Guance Cloud / 观测云 to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.