Guance Cloud MCP. Instantly query infrastructure metrics and events.
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Guance Cloud MCP Server gives your AI client direct access to your entire observability stack. It lets you list monitors, retrieve dashboard configurations, browse real-time events, and run Data Query Language (DQL) statements—all via natural conversation.
You manage your infrastructure data and troubleshoot outages without ever opening the Guance console. This is for SREs and DevOps teams who need instant, deep insight into system health.
What your AI agents can do
Get billing
Retrieves the current billing usage details for the workspace.
Get event
Fetches specific details about an observed system event.
Get monitor
Retrieves the detailed configuration and status of a single system monitor.
List all configured monitors and retrieve details on specific alerts or system health rules.
Browse real-time and historical observability events, like errors and critical system changes, without manual dashboard filtering.
Execute powerful Data Query Language (DQL) statements to pull specific metrics, logs, or performance data.
Retrieve metadata about the workspace, list all dashboards, and check billing usage or API keys.
Ask AI about this MCP
Supported MCP Clients
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Guance Cloud MCP Server: 10 Tools for Observability
These tools give your AI agent direct access to Guance Cloud's monitoring, logging, and billing data. Use them to get immediate, actionable insights into your system's performance.
019d8444get billing
Retrieves the current billing usage details for the workspace.
019d8444get event
Fetches specific details about an observed system event.
019d8444get monitor
Retrieves the detailed configuration and status of a single system monitor.
019d8444get workspace
Gets core metadata and status information for the entire cloud workspace.
019d8444list access keys
Lists all API access keys configured for the workspace.
019d8444list dashboards
Lists every dashboard available in the workspace.
019d8444list events
Lists recent observability events from the workspace.
019d8444list log sources
Lists all available log data sources for querying.
019d8444list monitors
Lists the names and status of all system monitors.
019d8444query data
Runs a Data Query Language (DQL) query against the platform to pull specific metrics or logs.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Guance Cloud / 观测云, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Your AI client gets direct access to your whole observability stack. You can list all system monitors and check their configurations using list_monitors and get_monitor. You can also get core metadata about the whole cloud workspace with get_workspace.
Need to see what's going on? You can list recent observability events with list_events, and if you need details on a specific incident, get_event fetches those details. Want to dig into what's happening right now? You can run specific data queries using query_data with Data Query Language (DQL) statements, or list all available log data sources with list_log_sources.
Want to check the bigger picture? You can list every dashboard available in the workspace via list_dashboards. You can also audit your API keys by calling list_access_keys, and check the billing usage details for the workspace using get_billing.
It's built for SREs and DevOps teams who need instant, deep insight into system health. You manage your infrastructure data and troubleshoot outages without ever opening the Guance console.
How Guance Cloud MCP Works
- 1 Subscribe to the Guance Cloud MCP Server and provide your Guance Cloud API Key (DF-API-KEY).
- 2 Your AI agent sends a natural language request (e.g., 'What is the average CPU usage last week?').
- 3 The agent uses the appropriate tool (e.g.,
query_data) to call the Guance API, and you receive the specific metrics or list of events.
The bottom line is that your AI client turns the complex, multi-step process of observability into a single, conversational command.
Who Is Guance Cloud MCP For?
This is for the SRE and DevOps engineer who gets tired of clicking through dashboards at 2 AM. It's for the Infra Lead who needs to audit configurations without touching a console. If your job involves correlating alerts, logs, and metrics across systems, this tool saves you hours of manual investigation.
Automating incident response and querying system health metrics via natural language during an outage.
Coordinating monitoring strategies and running log analysis against system events.
Retrieving specific system metrics or performing deep log analysis using a unified AI interface.
What Changes When You Connect
- See the status of all monitors instantly. Instead of clicking through the 'Monitors' section, just ask the agent to
list_monitors. You get a list of all active alerts and their current state in seconds. - Deep-dive into metrics using DQL. The
query_datatool lets you run complex queries—like 'average CPU usage last week'—without writing boilerplate API calls or building a custom dashboard. - Audit your setup easily. Use
list_dashboardsorget_workspaceto retrieve metadata and status information for your entire environment, perfect for compliance checks. - Track every system change.
list_eventsgives you a real-time feed of errors, alerts, and system changes. You can then useget_eventto get full details on a critical incident. - Manage credentials from chat. You can use
list_access_keysto see which API keys are active and useget_billingto check usage limits—all without leaving your AI interface. - Coordinate monitoring strategy. You can use
get_monitorto check the configuration of a specific monitor, ensuring it's set up correctly before a deployment.
Real-World Use Cases
Investigating a Production Outage
The system is down. Instead of jumping between the 'Alerts' dashboard and the 'Logs' tab, you ask your agent: 'List all monitors and find the last critical event.' The agent runs list_monitors and list_events, correlating the data points and telling you exactly where the failure originated.
Auditing Resource Usage
Compliance requires proof of resource usage. You ask your agent to 'Show the billing usage for the last quarter.' The agent runs get_billing and list_dashboards, pulling the necessary usage metrics and dashboard metadata into a single, reportable answer.
Comparing System Performance
You need to know if the recent code deployment impacted latency. You ask your agent to 'Query average API latency for the 'Production' cluster.' The agent uses query_data to execute the DQL statement and provides the precise, time-series metric you need.
Onboarding a New Team Member
A new engineer needs to know the system's current status. You ask your agent to 'List all monitors and give me the core workspace details.' The agent runs list_monitors and get_workspace to provide a comprehensive, immediate status report.
The Tradeoffs
Manual Console Navigation
Jumping through the Guance console: opening the monitors list, clicking on an alert, then opening the event stream, then manually running a query in a separate tab. This takes 15 minutes and requires copying multiple IDs.
→
Keep it in the chat. Ask your agent: 'Show me the status of the 'High CPU Alert' and the corresponding events.' The agent uses get_monitor and list_events to correlate the data and give you the full picture in one response.
Ignoring Data Context
Running a query like 'Show me the CPU usage' without specifying the time range or cluster, leading to ambiguous or incomplete data sets.
→
Always be specific. Tell your agent: 'Use query_data to find the average CPU usage across the 'Production' cluster for the last 3 hours.' This forces the agent to use the correct parameters.
Over-relying on Visualizations
Accepting a dashboard view as the final answer, but needing the raw data points for a report or a deeper calculation.
→
Get the raw numbers. Use query_data to execute the DQL query. This pulls the exact metrics and logs you need, allowing you to export or analyze the data outside the platform.
When It Fits, When It Doesn't
Use this if you need to act on observability data. You need to check the status of an alert, pull raw metrics for a report, or list out all components for an inventory audit. For example, if you need to know if a monitor is broken, use get_monitor. If you need to see all the logs related to that failure, use list_events and query_data. Don't use this if you just want to browse data—use the platform's native dashboarding tools instead. This server is for deep, actionable data retrieval, not simple viewing.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Guance Cloud / 观测云. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Sifting through alerts and logs is a massive waste of time.
Today, troubleshooting means a manual loop: you find an alert in the dashboard, copy the ID, jump to the event log, search by that ID, and then manually run a query to see the metric trend. You end up switching between 4 different tabs and copy-pasting IDs until you find the root cause.
With this MCP server, you just tell your agent: 'I have an issue with X component.' It runs `list_monitors` to find the alert, runs `list_events` to find the timeline, and executes `query_data` to pull the performance trend. You get the full story, instantly.
Guance Cloud MCP Server: Get the full observability picture.
Forget manually checking API keys or billing limits. You can ask the agent to 'What are my current billing limits and what keys do I have?' It runs `get_billing` and `list_access_keys` and gives you a clear, combined answer. It's all one prompt.
This means you stop treating monitoring as a series of disconnected tasks. You treat it as one continuous conversation. Your agent connects the monitoring status, the logs, and the usage data seamlessly.
Common Questions About Guance Cloud MCP
How do I check the status of my system monitors using the get_monitor tool? +
Use the agent to retrieve the monitor details. You need to provide the specific monitor ID or name when prompted. The tool returns the current status, configuration, and last check time for that monitor.
Can I query data using the query_data tool if I don't know the exact log source? +
No. You must first use list_log_sources to see what data is available. Then, you can structure your DQL query to target those specific, listed sources.
What is the difference between list_events and list_monitors? +
The difference is scope. list_monitors checks if your defined system rules are firing alerts. list_events shows a chronological stream of every recorded action, error, or system change that happened.
How do I use the get_workspace tool? +
Use get_workspace when you need high-level metadata. It provides foundational details about the entire Guance Cloud environment, like its creation date or overall status, rather than specific metrics.
Does the get_billing tool help with cost optimization? +
Yes, it reports your current billing usage. This lets you track costs and identify if specific services or high-volume logs are driving up your spend.
How do I list all available dashboards using the list_dashboards tool? +
The list_dashboards tool retrieves a list of all dashboard IDs and names. You then use the get_monitor or query_data tools to fetch the specific configurations or metrics for a selected dashboard.
What information does the list_log_sources tool provide? +
The list_log_sources tool lists every available log data source connected to your workspace. This lets you know exactly where to direct your query_data requests for specific log analysis.
What should I do if the get_event tool fails or returns an error? +
If get_event fails, check your API key validity or verify the event ID you are querying. You can also use the list_events tool first to confirm the event exists before attempting to get details.
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.
What is DQL? +
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.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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