Bring Real Time Monitoring
to LangChain
Learn how to connect Netdata to LangChain and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Netdata MCP Server?
Connect your Netdata monitoring infrastructure to any AI agent for instant, real-time observability and performance analysis through natural language.
What you can do
- Real-time Metrics — Fetch granular data from specific charts (CPU, RAM, Disk, Network) using
get_chart_datato diagnose performance bottlenecks. - Agent Health — Inspect node versions, host information, and enabled features with
get_agent_infoandlist_charts. - Alert Management — Query active alarms on local agents via
get_alarmsor monitor space-wide critical issues usinglist_space_alerts. - Cloud Orchestration — Navigate your entire infrastructure by listing spaces, rooms, and nodes connected to Netdata Cloud.
- Scraping & Export — Retrieve all metrics in a format suitable for external analysis tools using
get_all_metrics.
How it works
- Subscribe to this server
- Enter your Netdata Cloud Token or Agent URL
- Start monitoring your infrastructure from Claude, Cursor, or any MCP-compatible client
No more jumping between dashboards to find which node is spiking. Your AI acts as a 24/7 SRE or System Administrator.
Who is this for?
- DevOps Engineers — instantly correlate system alerts with recent deployments without leaving the terminal or IDE.
- SREs — automate the retrieval of chart data and alarm statuses to speed up incident response.
- System Administrators — manage large-scale node environments by querying spaces and rooms via simple conversation.
Built-in capabilities (10)
Get Netdata Agent information
Get current status of all configured alarms
Get all metrics for scraping
Fetch metric data from a specific chart
). List all available charts on the node
List nodes within a specific room
List rooms within a specific space
Fetch active alerts across the space
List all nodes connected to a space
List all Netdata Cloud spaces
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Netdata 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.
- —
The largest ecosystem of integrations, chains, and agents. combine Netdata 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 Netdata queries for multi-turn workflows
Netdata in LangChain
Netdata and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Netdata to LangChain through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Netdata in LangChain
The Netdata 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. All 10 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LangChain only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Netdata for LangChain
Every tool call from LangChain to the Netdata MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I fetch specific metric data for a chart like CPU usage?
Use the get_chart_data tool. You need to provide the chart ID (e.g., 'system.cpu') and optionally specify time ranges like after or aggregation methods like group.
Can I see all active alerts across my entire Netdata Cloud space?
Yes! Use the list_space_alerts tool with your space_id. It will return all active alerts across all nodes connected to that specific Cloud space.
How do I list all the nodes available in a specific room?
Use the list_room_nodes tool. You will need to provide both the space_id and the room_id to filter the nodes within that specific grouping.
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.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters
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