Netdata MCP. Get Real-Time Infra Metrics and Alerts Instantly
Netdata MCP connects your entire infrastructure monitoring suite to any AI client. Instantly pull real-time performance metrics, check current system alerts, and get deep operational data for specific nodes or across entire cloud spaces. Your agent reads the raw numbers so you don't have to click through dozens of dashboards.
Give Claude and any AI agent real-world access
Fetch detailed metric readings—like CPU load or disk usage—for a specific component on a machine.
Check for active warnings and alarms, either on a single local agent or across an entire cloud environment.
List all connected spaces, rooms, and individual nodes to understand your full monitoring scope.
Collect every available metric across the monitored nodes into a single dataset for external processing.
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What AI agents can do with Netdata MCP: 10 Tools for Monitoring
Use these tools in conversation with your AI agent to query everything from specific charts to entire cloud space alert statuses.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Netdata MCPGet Alarms
Retrieves the current status of every configured alarm on a machine.
Get All Metrics
Gathers all available performance metrics into one bulk dataset for scraping or...
List Charts
Provides a list of every metric chart currently tracked on the connected node.
Get Chart Data
Fetches specific time-series data points from any requested performance chart.
Get Agent Info
Returns detailed information, including the version and host details, for the...
List Room Nodes
Lists all individual nodes belonging to a specific monitored room.
List Rooms
Provides a list of all rooms within a defined monitoring space.
List Space Alerts
Aggregates and reports on critical issues across the entire monitored cloud space.
List Space Nodes
Lists all machines connected under a specific monitoring space.
List Spaces
Retrieves a comprehensive list of all available Netdata Cloud spaces.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
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 each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Netdata, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Netdata. 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.
VINKIUS CLOUD
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
The Dashboard Overload Problem
Today, finding out why a service is slow means logging into dashboard A to check CPU, then switching to dashboard B to see disk I/O. If you need to know about alerts, you open dashboard C. You end up copy-pasting data across spreadsheets just to build a picture of the problem.
With this MCP, all those separate views disappear. You simply ask your agent what's wrong with the service. It correlates metrics from CPU and disk checks, reports on any active alarms via `get_alarms`, and gives you one single answer right in your chat window.
Get Actionable Insights with Netdata MCP
You stop manually checking node versions using the agent's ability to run `get_agent_info`. You don't have to track down which spaces are connected; listing them all via `list_spaces` is instant.
The difference is that you get direct, real-time answers. Your AI client acts as a system expert who has already checked every tab for you.
What Netdata MCP does for your AI
Your AI client can connect directly to Netdata to give you instant visibility into your infrastructure's performance. Instead of jumping between monitoring tabs, you ask a question—like 'Why is CPU spiking on Node Alpha?'—and get an immediate answer backed by real data. You can fetch granular metrics for specific components like RAM or network throughput using one command.
Need to know if something is broken? Your agent checks active alarms across your local machines or even monitors critical issues space-wide. When you're ready to analyze the raw numbers, you retrieve all collected metrics in a format that external tools love. This makes troubleshooting faster and less painful. Through Vinkius, you connect this powerful MCP with any compatible client, giving your agent 24/7 System Administrator capabilities right where you work.
019e38c7-3a25-7353-8181-983dc35217b4 How to set up Netdata MCP
The bottom line is you get immediate operational insights without ever leaving your IDE or terminal.
Subscribe to this MCP and provide your Netdata Cloud Token or Agent URL.
Your AI client accesses the connection details, giving it visibility into all connected nodes and spaces.
You prompt your agent with a question (e.g., 'What are the current disk alerts?') and receive specific, actionable data.
Who uses Netdata MCP
This MCP is for ops engineers who spend too much time clicking through dashboards at 2 AM. It's essential for SREs and System Administrators managing large, complex environments that require instant data correlation.
Correlate system alerts with recent deployments by asking your agent to check current alarms against deployment logs.
Speed up incident response by having the MCP automatically gather specific chart data or list critical space-wide issues.
Manage multi-node environments efficiently by listing all connected spaces and rooms via simple conversation prompts.
Benefits of connecting Netdata MCP
Instant bottleneck diagnosis: Instead of guessing, ask your agent to fetch metric data from a specific chart using get_chart_data to pinpoint exactly where performance is dipping.
Centralized alert visibility: Check for local machine issues with get_alarms, or get a high-level view of critical alerts across the whole space using list_space_alerts.
Full inventory mapping: Never lose track of your assets. Use list_spaces and list_rooms to map out every node connected through your infrastructure.
Historical data analysis: Need to feed metrics into a custom tool? Run get_all_metrics to pull all raw performance numbers for deep external processing.
Quick health checks: Before starting an investigation, run get_agent_info to confirm the version and basic status of the agent itself.
Netdata MCP use cases
Investigating a sudden network slowdown
The user asks their agent about recent network issues. The agent checks list_space_nodes to identify all relevant machines, then uses get_chart_data on the network metrics for those nodes. It returns specific data confirming which machine is spiking and why.
Performing a routine system audit
The user needs a full picture of the environment. The agent first calls list_spaces to see all environments, then uses list_rooms to drill down into each one, building a complete map of connectivity.
Responding to an urgent production alarm
A critical alert hits. The user prompts the agent for active alarms using get_alarms. The agent immediately returns which specific component is failing and whether other system health checks are clear, saving minutes of manual investigation.
Preparing data for a quarterly report
The team needs historical performance metrics. Instead of exporting manually from dashboards, the user runs get_all_metrics, getting all raw data in one go that can be fed directly into reporting tools.
Netdata MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Manually checking every dashboard
A sysadmin has to open 15 different tabs, click through menus, and copy/paste metrics from CPU graphs, RAM graphs, and disk status pages one by one.
Ask your agent to run list_space_nodes first. Then ask it to fetch the specific performance data using get_chart_data. It handles the navigation for you.
Ignoring high-level alerts
The system is failing due to a critical, space-wide issue, but the engineer only checks the local machine's dashboard and misses the root cause.
Always run list_space_alerts first. This function aggregates issues across all connected nodes and gives you the full picture immediately.
Confusing metrics with inventory
The user asks 'What is wrong?' but doesn't know if they need a metric check or an asset list, leading to vague results.
If you suspect poor performance, use get_chart_data. If you just need to map your infrastructure, use the combination of list_spaces, list_rooms, and list_space_nodes.
When to use Netdata MCP
Use this MCP if your job involves high-volume incident response or managing environments with dozens of nodes. You need a single point of access that can query metrics, check alerts, and map out the topology without you having to click through UIs. Don't use it if you only need to view one specific metric (like just CPU). For simple checks, just viewing charts might be enough. But if you need correlation—for instance, 'Show me all nodes in Space X that have active alerts AND whose RAM usage was over 90% last hour'—then this MCP is your only option. It combines the functions of get_alarms, list_space_nodes, and get_chart_data into one conversational flow.
Frequently asked questions about Netdata MCP
How do I check all nodes connected to my environment using Netdata MCP? +
You can list all spaces first using list_spaces. Then, drill down into the rooms and finally use list_space_nodes to get a complete inventory of every machine monitored.
Can I check for active alarms with Netdata MCP? +
Yes. You can run get_alarms to see local warnings, or you can use list_space_alerts if you need a summary of critical issues across the entire cloud space.
What data do I get when I use get_chart_data with Netdata MCP? +
You get specific, time-series metric readings for any chart type, like CPU or RAM. This allows you to diagnose performance bottlenecks precisely rather than just seeing a general graph.
Does Netdata MCP help me analyze historical data? +
Yes, you can use get_all_metrics to retrieve all collected metrics in a format designed for external analysis tools, making history accessible.
Is Netdata MCP just for Linux servers? +
The MCP is designed to work with your configured Netdata Agent. It accesses the data available through that specific agent connection.