Netdata MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Get Agent Info, Get Alarms, Get All Metrics, and more

Name: Netdata
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Netdata as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The Netdata MCP Server for LlamaIndex is a standout in the Cloud Infrastructure category — giving your AI agent 10 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Netdata. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Netdata?"
    )
    print(response)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 Netdata MCP Server

Connect your Netdata monitoring infrastructure to any AI agent for instant, real-time observability and performance analysis through natural language.

LlamaIndex agents combine Netdata tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Real-time Metrics — Fetch granular data from specific charts (CPU, RAM, Disk, Network) using get_chart_data to diagnose performance bottlenecks.
Agent Health — Inspect node versions, host information, and enabled features with get_agent_info and list_charts.
Alert Management — Query active alarms on local agents via get_alarms or monitor space-wide critical issues using list_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.

The Netdata MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 10 Netdata tools available for LlamaIndex

When LlamaIndex connects to Netdata through Vinkius, your AI agent gets direct access to every tool listed below — spanning real-time-monitoring, infrastructure-observability, system-metrics, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get agent info on Netdata

Get Netdata Agent information

get

Get alarms on Netdata

Get current status of all configured alarms

get

Get all metrics on Netdata

Get all metrics for scraping

get

Get chart data on Netdata

Fetch metric data from a specific chart

list

List charts on Netdata

). List all available charts on the node

list

List room nodes on Netdata

List nodes within a specific room

list

List rooms on Netdata

List rooms within a specific space

list

List space alerts on Netdata

Fetch active alerts across the space

list

List space nodes on Netdata

List all nodes connected to a space

list

List spaces on Netdata

List all Netdata Cloud spaces

Connect Netdata to LlamaIndex via MCP

Follow these steps to wire Netdata into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Netdata

Why Use LlamaIndex with the Netdata MCP Server

LlamaIndex provides unique advantages when paired with Netdata through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Netdata tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Netdata tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Netdata, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Netdata tools were called, what data was returned, and how it influenced the final answer

Netdata + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Netdata MCP Server delivers measurable value.

Hybrid search: combine Netdata real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Netdata to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Netdata for fresh data

Analytical workflows: chain Netdata queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Netdata in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Netdata immediately.

"Get the current information and version of the Netdata agent."

"List all available charts on this node so I can see what metrics are being collected."

"Are there any active alarms or warnings on the local agent right now?"

Troubleshooting Netdata MCP Server with LlamaIndex

Common issues when connecting Netdata to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Netdata + LlamaIndex FAQ

Common questions about integrating Netdata MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Netdata tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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