How do I find my Guance Cloud API Key?

Log in to your Guance Cloud workspace, navigate to [Management] → [API Key Management], and generate a new key. Use the provided value as your DF-API-KEY.

Data Query Language (DQL) is the query syntax used by Guance Cloud to retrieve metrics, logs, and other observability data. You can use the `query_data` tool to execute these statements.

Can I check my data usage via the agent?

Yes. Use the `get_billing` tool to retrieve current data usage and billing statistics for your workspace, helping you manage costs and resource allocation.

Guance Cloud / 观测云 MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Guance Cloud / 观测云
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Guance Cloud / 观测云 through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "guance-cloud": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Guance Cloud / 观测云, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Guance Cloud / 观测云 through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Guance Cloud / 观测云 MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Guance Cloud / 观测云 via MCP

Why Use LangChain with the Guance Cloud / 观测云 MCP Server

LangChain provides unique advantages when paired with Guance Cloud / 观测云 through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Guance Cloud / 观测云 MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Guance Cloud / 观测云 queries for multi-turn workflows

Guance Cloud / 观测云 + LangChain Use Cases

Practical scenarios where LangChain combined with the Guance Cloud / 观测云 MCP Server delivers measurable value.

RAG with live data: combine Guance Cloud / 观测云 tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Guance Cloud / 观测云, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Guance Cloud / 观测云 tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Guance Cloud / 观测云 tool call, measure latency, and optimize your agent's performance

Guance Cloud / 观测云 MCP Tools for LangChain (10)

These 10 tools become available when you connect Guance Cloud / 观测云 to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

Common issues when connecting Guance Cloud / 观测云 to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Guance Cloud / 观测云 + LangChain FAQ

Common questions about integrating Guance Cloud / 观测云 MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.