Which integrations are available for this server?

Provides pre-configured dashboards for visualizing network performance and health metrics. Exposes network telemetry metrics at a /metrics endpoint for Prometheus to scrape and alert on.

How do I use NetPulse?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@NetPulse Give me a network health summary" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

NetPulse

by hind77

Overview Schema Related Servers Score Discussions

Python

NetPulse 🌐

Python 3.11+ License: MIT Tests MCP

An MCP server that exposes live network monitoring data as Resources and diagnostic capabilities as Tools, letting AI assistants query network health conversationally.

NetPulse bridges the gap between traditional network monitoring and AI-powered operations. It implements the Model Context Protocol (MCP) to give AI assistants like Claude real-time access to network telemetry — device status, interface metrics, latency measurements, bandwidth utilization, and active alerts — all through a clean, structured API.

Architecture

graph TB
    subgraph "AI Layer"
        Claude["Claude Desktop / MCP Client"]
    end

    subgraph "NetPulse MCP Server"
        Server["server.py<br/>FastMCP"]
        Resources["Resources<br/>6 data endpoints"]
        Tools["Tools<br/>6 diagnostic actions"]
        Prompts["Prompts<br/>3 workflow templates"]
        Sim["Network Simulator<br/>7 virtual devices"]
        Metrics["Prometheus Exporter<br/>/metrics"]
    end

    subgraph "Observability Stack"
        Prom["Prometheus"]
        Graf["Grafana"]
    end

    Claude <-->|MCP Protocol| Server
    Server --> Resources
    Server --> Tools
    Server --> Prompts
    Resources --> Sim
    Tools --> Sim
    Sim --> Metrics
    Metrics --> Prom
    Prom --> Graf

    style Claude fill:#6B48FF,color:#fff
    style Server fill:#0EA5E9,color:#fff
    style Sim fill:#10B981,color:#fff
    style Graf fill:#F59E0B,color:#fff

Data Flow

Network Simulator generates realistic, time-varying metrics for 7 virtual devices
MCP Resources expose read-only telemetry data (device status, interfaces, latency, bandwidth, topology, alerts)
MCP Tools provide executable diagnostics (ping, traceroute, interface check, config viewer, baseline comparison, interface restart)
MCP Prompts offer guided workflows (health briefing, troubleshooting, capacity planning)
Prometheus + Grafana provide visual dashboards alongside the AI interface

Related MCP server: LogicMonitor MCP Server

Quick Start

1. Clone the repository

git clone https://github.com/yourusername/netpulse.git
cd netpulse

2. Launch the full stack

docker compose up -d

This starts:

NetPulse MCP Server on port 8080 (SSE transport)
Prometheus on port 9091
Grafana on port 3000 (login: admin / netpulse)

3. Connect Claude Desktop

Add to your Claude Desktop MCP configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "netpulse": {
      "command": "python",
      "args": ["-m", "netpulse.server"],
      "cwd": "/path/to/netpulse"
    }
  }
}

Or for SSE transport:

{
  "mcpServers": {
    "netpulse": {
      "url": "http://localhost:8080/sse"
    }
  }
}

Now ask Claude: "Give me a network health summary" — and watch it query real telemetry!

MCP Interface Reference

Resources (Read-Only Data)

URI	Description
`netpulse://devices/status`	Status of all 7 monitored devices with CPU, memory, temperature
`netpulse://interfaces/{device}`	Interface metrics for a specific device
`netpulse://latency/report`	Latency matrix between all connected endpoints
`netpulse://bandwidth/top-talkers`	Top 10 bandwidth consumers
`netpulse://topology/map`	Network topology as nodes + edges with health status
`netpulse://alerts/active`	Currently firing alerts with severity

Tools (Executable Actions)

Tool	Description	Key Parameters
`ping_device`	Ping a device and get RTT stats	`target`, `count`
`run_traceroute`	Trace network path to destination	`target`, `max_hops`
`check_interface`	Detailed interface diagnostics	`device`, `interface`
`get_device_config`	View device running configuration	`device`, `section`
`compare_baseline`	Compare current vs historical baseline	`device`, `metric`, `window`
`restart_interface`	Bounce an interface (requires confirmation)	`device`, `interface`, `confirm`

Prompts (Workflow Templates)

Prompt	Description	Arguments
`network_health_summary`	NOC morning briefing workflow	None
`troubleshoot_connectivity`	Guided connectivity diagnosis	`source`, `destination`
`capacity_planning`	Bandwidth analysis and projections	None

Configuration

Environment Variables

Variable	Default	Description
`NETPULSE_HOST`	`0.0.0.0`	Server bind address
`NETPULSE_PORT`	`8080`	MCP server port
`NETPULSE_TRANSPORT`	`stdio`	Transport mode (`stdio` or `sse`)
`NETPULSE_LOG_LEVEL`	`INFO`	Logging level
`NETPULSE_POLL_INTERVAL`	`30`	Metric polling interval (seconds)

Device Inventory

Edit src/netpulse/config/devices.yaml to customize the simulated network topology. The default includes 7 devices across 2 data centers and a branch office.

Thresholds

Edit src/netpulse/config/thresholds.yaml to adjust alerting thresholds for CPU, memory, latency, packet loss, bandwidth, and temperature.

Fault Injection (Demo)

Inject faults to demonstrate AI-driven incident detection:

# Take down the WAN link
python -m netpulse.simulators.fault_injector --scenario link_down

# Spike CPU on the core router
python -m netpulse.simulators.fault_injector --scenario cpu_spike

# Simulate interface flapping
python -m netpulse.simulators.fault_injector --scenario interface_flap

# Take down a device
python -m netpulse.simulators.fault_injector --scenario device_down

# Saturate bandwidth
python -m netpulse.simulators.fault_injector --scenario bandwidth_saturation

Then ask Claude: "Are there any network issues right now?"

Development

Local Setup

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows

# Install with dev dependencies
pip install -e ".[dev]"

# Run the server locally (stdio mode)
python -m netpulse.server

Running Tests

pytest --cov=netpulse --cov-report=term-missing

Code Quality

# Linting
ruff check src/ tests/

# Type checking
mypy src/netpulse/

Simulated Network Topology

          ┌─────────────┐          ┌─────────────┐
          │ core-rtr-01  │◄────────►│ core-rtr-02  │
          │  10.0.0.1    │ 10Gbps  │  10.0.0.2    │
          │  Data Ctr A  │backbone │  Data Ctr B  │
          └──┬──────┬────┘          └──────┬───────┘
             │      │                      │
        10G  │      │ 100M            10G  │
             │      │                      │
     ┌───────┴──┐   │              ┌───────┴──┐
     │dist-sw-01│   │              │dist-sw-02│
     │ 10.0.1.1 │   │              │ 10.0.1.2 │
     └─────┬────┘   │              └──────────┘
           │        │
      1G   │        │
           │        │
     ┌─────┴────┐   │         ┌───────────┐
     │edge-fw-01│   └────────►│ wan-rtr-01 │
     │ 10.0.2.1 │     WAN    │  10.0.4.1  │
     └──────────┘             └──────┬─────┘
                                     │ 1G
                              ┌──────┴──────┐
                              │access-sw-01 │
                              │  10.0.3.1   │
                              │ Branch Off 1│
                              └─────────────┘

Author

Hind Boukhairat — IoT dev specializing in network monitoring and AIOps, transitioning into AI Integration Engineering. Holder of two MCP certifications from Anthropic/Skilljar (Introduction + Advanced Topics).

NetPulse is part of a portfolio showcasing the intersection of telecom/network operations and AI orchestration.

License

MIT — see LICENSE for details.

Available Tools

6 tools

check_interfaceB

Get detailed diagnostic information for a specific interface.

Args: device: Hostname of the network device. interface: Interface name (e.g., GigabitEthernet0/0).

ParametersJSON Schema

Name	Required	Description	Default
`device`	Yes
`interface`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

B3.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It only states it 'get detailed diagnostic information' without mentioning side effects, permissions required, or what happens if device is unreachable. Vague.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loads the purpose, and uses a clear structure with Args list. However, it could be slightly more succinct.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists, return value explanation is not needed. But for a 2-parameter tool with no usage guidance, the description is moderately complete but lacks behavioral details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description adds value by explaining both parameters: 'device: Hostname of the network device. interface: Interface name (e.g., GigabitEthernet0/0).' This provides clear format and examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get detailed diagnostic information for a specific interface.' The verb 'get' and resource 'interface' are specific, but it does not explicitly differentiate from sibling tools like ping_device or run_traceroute.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like ping_device or restart_interface. No when-not-to-use or prerequisite conditions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

compare_baselineA

Compare a device's current metric value against its rolling baseline.

Args: device: Hostname of the network device. metric: Metric name (cpu_percent, memory_percent). window: Baseline window (for display context, default '24h').

ParametersJSON Schema

Name	Required	Default
`device`	Yes
`metric`	Yes
`window`	No	24h

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A3.5/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must fully disclose behavioral traits. It only states the high-level operation, omitting details like what happens on missing device, invalid metric, or whether the operation is read-only. The term 'rolling baseline' is not explained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: one sentence for purpose and three short lines for parameters. No extraneous text, every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the existence of an output schema, the description does not need to detail return values, but it should clarify what 'compare' means (e.g., difference, percentage). The description is minimal and assumes agent knowledge of baselines.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, but the description compensates by adding semantics: device is 'hostname', metric lists allowed values (cpu_percent, memory_percent), window has default and display purpose. This adds needed meaning beyond the schema's type-only fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: comparing a device's current metric value against its rolling baseline. It uses a specific verb ('compare') and resource ('metric value against baseline'), and is distinct from sibling tools like ping_device or get_device_config.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or situations where the tool is applicable or not.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_device_configA

Retrieve the running configuration of a network device (read-only).

Args: device: Hostname of the network device. section: Config section (e.g., 'bgp', 'ospf'). Returns full config if empty.

ParametersJSON Schema

Name	Required	Description	Default
`device`	Yes
`section`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavioral traits. It correctly states 'read-only', but does not mention authentication requirements, error handling, rate limits, or impact on the device. The read-only claim is the only behavioral insight, which is sufficient but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: one sentence for purpose plus two bullet-point parameter explanations. Every sentence adds value; no filler. The main action is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity and the presence of an output schema (which likely documents return structure), the description is nearly complete. It covers the core operation and parameter semantics. It omits potential error scenarios or prerequisites, but for a read-only retrieval tool, the missing details are minor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has no descriptions (0% coverage), but the tool description compensates by explaining each parameter: 'device' as hostname, 'section' with examples ('bgp', 'ospf') and behavior (returns full config if empty). This adds meaning beyond the schema's bare types and titles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Retrieve' and the resource 'running configuration of a network device'. It explicitly marks the operation as 'read-only', which distinguishes it from mutating siblings like restart_interface. The domain (network device) is precise.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains parameters (device and section) and their behavior (e.g., section examples, default full config), but does not provide explicit guidance on when to choose this tool over siblings like compare_baseline or check_interface. Usage context is implied by the tool's purpose, but no when-not or alternative references are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

ping_deviceA

Ping a network device and return round-trip time statistics.

Args: target: IP address or hostname to ping. count: Number of ping packets to send (1-20, default 5).

ParametersJSON Schema

Name	Required	Description	Default
`count`	No
`target`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A3.9/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It states the tool pings and returns statistics, but does not mention prerequisites (e.g., network access, permissions) or potential side effects (e.g., timeouts). The core behavior is clear but not fully transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences plus parameter explanations. It is front-loaded with the purpose and contains no superfluous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 parameters, output schema present, no annotations), the description adequately covers purpose, parameter semantics, and expected output (round-trip stats). No critical information is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates by explaining the 'target' parameter as an IP address or hostname and 'count' with a range and default. This adds meaningful context beyond the schema's type and default values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pings a network device and returns round-trip time statistics. It uses a specific verb ('Ping') and resource ('network device'), distinguishing it from sibling tools like run_traceroute or check_interface.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as run_traceroute or check_interface. The description focuses on parameters but lacks context on selection criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

restart_interfaceA

Restart (bounce) a network interface. REQUIRES explicit confirmation.

This is a state-modifying action. You MUST set confirm=true to execute. If confirm is false or missing, an impact analysis is returned instead.

Args: device: Hostname of the network device. interface: Interface name to restart (e.g., GigabitEthernet0/0). confirm: Must be explicitly set to true to execute the restart.

ParametersJSON Schema

Name	Required	Description	Default
`device`	Yes
`confirm`	No
`interface`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully discloses that it is a state-modifying action, requires confirmation, and details the dual behavior (impact analysis vs. execution) based on the confirm parameter.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear header, warnings, and a parameter list. Every sentence provides essential information without redundancy, making it efficient for an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (3 parameters, no annotations), the description is highly complete. It covers purpose, behavior, parameters, and output (impact analysis), even though an output schema exists. No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description thoroughly explains all three parameters: device, interface, and confirm. It adds meaning by stating the interface format example and that confirm must be explicitly true to execute.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Restart (bounce) a network interface.' It distinguishes this from sibling tools (e.g., check_interface, ping_device) by specifying a state-modifying action that restarts an interface.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly requires explicit confirmation, explains the behavior when confirm is false (impact analysis), and sets clear usage conditions. It does not directly name alternatives but the sibling context provides differentiation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

run_tracerouteA

Run a simulated traceroute to a network device.

Args: target: IP address or hostname of the destination. max_hops: Maximum number of hops (1-64, default 30).

ParametersJSON Schema

Name	Required	Description	Default
`target`	Yes
`max_hops`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A3.5/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description labels the traceroute as 'simulated,' hinting it may not be a real network operation, but provides no further behavioral details (e.g., permissions, side effects, rate limits, failure modes). With no annotations, the agent gets minimal transparency beyond the word 'simulated.'

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise: one-line purpose followed by parameter docs. Every sentence is necessary. No verbosity, properly front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter tool with an output schema, the description covers basic purpose and params. However, it omits the output format/behavior (even though output schema exists, the description could still hint at what to expect), and the 'simulated' aspect is not explained. Minor gaps prevent full completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds substantial meaning to both parameters: 'target' is clarified as 'IP address or hostname,' and 'max_hops' gets range '(1-64, default 30).' Since the input schema has no descriptions (0% coverage), the description fully compensates for the missing semantic information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Run a simulated traceroute to a network device,' specifying the action (run), resource (traceroute), and scope (network device). The term 'simulated' adds a distinguishing nuance. While it doesn't explicitly differentiate from siblings, the purpose is specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., ping_device, check_interface). There is no mention of prerequisites, use cases, or conditions that favor traceroute over other diagnostic tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

6 tool updatesv0.1.0Jul 28, 2026
- First observedcheck_interface
- First observedcompare_baseline
- First observedget_device_config
- First observedping_device
- First observedrestart_interface
- First observedrun_traceroute

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A3.9/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: ping and traceroute for connectivity tests, interface diagnostics, config retrieval, baseline comparison, and interface restart. No overlap in functionality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., ping_device, run_traceroute, check_interface), with no mixing of styles or vague verbs.

Tool Count5/5

With 6 tools, the server is well-scoped for network diagnostic and management tasks. Each tool serves a distinct purpose without unnecessary bloat or gaps.

Completeness4/5

The set covers core network operations: connectivity test, path tracing, interface diagnostics, config retrieval, metric comparison, and a management action. Missing features like device listing or interface statistics are minor gaps for the intended domain.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

GitHub Repository

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