Mender MCP
M

Mender MCP

The Mender MCP server is an integration tool that connects AI assistants with the Mender IoT platform, supporting read - only operations such as device management, deployment monitoring, and system status query.
2 points
0

What is the Mender MCP Server?

The Mender MCP Server is a bridge that connects AI assistants (such as Claude Code) with the Mender IoT device management platform. It allows you to use natural language commands to monitor and manage your IoT devices, view device status, deployment progress, and system logs without leaving your development environment.

How to use the Mender MCP Server?

The usage process is divided into three simple steps: 1) Install the MCP server software. 2) Configure the Mender access token. 3) Set up the server connection in the AI assistant. After configuration, you can manage your IoT devices just like having a conversation with the assistant.

Applicable scenarios

Suitable for user groups such as IoT device operation and maintenance teams, DevOps engineers, and system administrators who need to monitor the status of a large number of devices, track deployment progress, and quickly troubleshoot device issues. Particularly suitable for medium - to large - scale deployment environments with dozens to thousands of IoT devices.

Main Features

Device Management
View device status in real - time, filter the device list, monitor device online status, and support filtering by multiple conditions such as status and device type.
Deployment Tracking
Monitor deployment progress, analyze success rates, view details of failed deployments, and stay informed about software update status in real - time.
Real - Time Monitoring
View device hardware specifications, system attributes, and custom inventory data to comprehensively understand device asset information.
Deployment Logs
Access detailed deployment log information, especially detailed error information for failed deployments, to facilitate quick troubleshooting.
Release Management
Browse available releases, view artifact details, check device compatibility, and manage the software release lifecycle.
Enterprise - Level Security
Token - based authentication, complete input validation, and read - only operation mode ensure system security and risk - free operation.
Audit Logs
View system audit logs, track user operations and system changes to meet compliance requirements.
Advantages
Natural language interaction: Manage complex IoT devices using simple conversations.
Seamless integration: Perfectly integrate with existing AI development environments without switching tools.
Real - time monitoring: Provide real - time views of device status and deployment progress.
Secure and reliable: Read - only operation mode avoids the risk of accidental device operations.
Multi - platform support: Compatible with both hosted and self - hosted Mender platforms.
Limitations
Read - only operation: Currently only supports monitoring functions and does not support device control operations.
Network dependency: Requires a stable network connection to access the Mender API.
Permission restrictions: Functions are limited by the Mender account permission configuration.
Learning curve: Requires basic knowledge of configuration and token management.

How to Use

Install the MCP Server
Create a Python virtual environment and install the Mender MCP server software package.
Get the Mender Access Token
Log in to the Mender platform, create a personal access token in the settings, and ensure it includes read permissions for device management and deployment management.
Configure the AI Assistant
Add server configuration in Claude Code or other MCP - supported AI assistants, providing the server URL and access token.
Start Using
Restart the AI assistant and start using natural language commands to manage your IoT devices.

Usage Examples

Device Status Monitoring
Quickly view the status distribution of all devices and identify offline or abnormal devices.
Deployment Progress Tracking
Monitor ongoing deployment tasks and understand the success rate and completion progress.
Fault Troubleshooting Analysis
When a deployment fails, quickly obtain detailed log information to analyze the failure cause.
Device Inventory Query
View the hardware configuration and system attribute information of a specific device.
Version Compatibility Check
Check the compatibility of a specific version with a device fleet.

Frequently Asked Questions

Why do I encounter a 401 authentication error?
How to securely store the access token?
Why can't I see the deployment logs?
Does it support the self - hosted Mender?
What are the permission requirements?

Related Resources

Mender Official Documentation
Complete official documentation and API reference for the Mender platform.
GitHub Code Repository
Source code and issue tracking for the Mender MCP server.
Model Context Protocol Specification
Official specification and implementation guide for the MCP protocol.
Mender Community Forum
Discussion and technical support forum for the Mender user community.

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "mender": {
      "command": "mcp-server-mender",
      "args": [
        "--server-url", "https://hosted.mender.io"
      ],
      "env": {
        "MENDER_ACCESS_TOKEN": "your_token_here"
      }
    }
  }
}

{
  "mcpServers": {
    "mender": {
      "command": "mcp-server-mender", 
      "args": [
        "--server-url", "https://hosted.mender.io",
        "--token-file", "~/.mender/token"
      ]
    }
  }
}

{
  "mcpServers": {
    "mender": {
      "command": "mcp-server-mender",
      "args": [
        "--server-url", "https://your-mender-server.company.com",
        "--token-file", "~/.mender/token"
      ]
    }
  }
}

{
  "mcpServers": {
    "mender": {
      "command": "mcp-server-mender",
      "args": [
        "--server-url", "https://hosted.mender.io",
        "--token-file", "~/.mender/token"
      ],
      "env": {
        "MCP_LOG_LEVEL": "DEBUG"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

M
MCP
The Microsoft official MCP server provides search and access functions for the latest Microsoft technical documentation for AI assistants
8.7K
5 points
A
Aderyn
Aderyn is an open - source Solidity smart contract static analysis tool written in Rust, which helps developers and security researchers discover vulnerabilities in Solidity code. It supports Foundry and Hardhat projects, can generate reports in multiple formats, and provides a VSCode extension.
Rust
5.9K
5 points
D
Devtools Debugger MCP
The Node.js Debugger MCP server provides complete debugging capabilities based on the Chrome DevTools protocol, including breakpoint setting, stepping execution, variable inspection, and expression evaluation.
TypeScript
5.4K
4 points
S
Scrapling
Scrapling is an adaptive web scraping library that can automatically learn website changes and re - locate elements. It supports multiple scraping methods and AI integration, providing high - performance parsing and a developer - friendly experience.
Python
7.8K
5 points
M
Mcpjungle
MCPJungle is a self-hosted MCP gateway used to centrally manage and proxy multiple MCP servers, providing a unified tool access interface for AI agents.
Go
0
4.5 points
C
Cipher
Cipher is an open-source memory layer framework designed for programming AI agents. It integrates with various IDEs and AI coding assistants through the MCP protocol, providing core functions such as automatic memory generation, team memory sharing, and dual-system memory management.
TypeScript
0
5 points
N
Nexus
Nexus is an AI tool aggregation gateway that supports connecting multiple MCP servers and LLM providers, providing tool search, execution, and model routing functions through a unified endpoint, and supporting security authentication and rate limiting.
Rust
0
4 points
S
Shadcn Ui MCP Server
An MCP server that provides shadcn/ui component integration for AI workflows, supporting React, Svelte, and Vue frameworks. It includes functions for accessing component source code, examples, and metadata.
TypeScript
12.1K
5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
16.6K
4.3 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
14.8K
4.5 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
24.5K
5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
44.7K
4.3 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
20.2K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
44.3K
4.5 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
30.2K
4.8 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
62.4K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2025AIBase