MCPInstall

raspberry-pi

by alphaonedevDevOps & Cloud

Compact Linux board for IoT, prototyping, and edge computing

Installs
98
Last 24h
—
Trending rank
—
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/alphaonedev/openclaw-graph --skill raspberry-pi
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads raspberry-pi automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

raspberry-pi

Purpose

This skill enables the AI to interact with Raspberry Pi devices for IoT tasks, including remote management, hardware prototyping, and edge computing operations.

When to Use

Use this skill for scenarios involving hardware setup, such as deploying sensors in a smart home, running lightweight servers for data processing, or testing embedded applications on a compact Linux board.

Key Capabilities

  • Establish SSH connections to execute commands on Raspberry Pi.
  • Configure hardware settings, like GPIO pins, for physical interactions.
  • Manage software installations and updates via apt.
  • Monitor system resources and logs for edge computing tasks.
  • Integrate with Python libraries for automation, e.g., RPi.GPIO for pin control.

Usage Patterns

To accomplish tasks, first authenticate via SSH using environment variables like $RASPI_HOST and $RASPI_SSH_KEY. Then, run commands directly or invoke scripts. For repeated tasks, wrap commands in Python functions. Always check device connectivity before proceeding. For GPIO work, import relevant libraries and set pin modes explicitly.

Common Commands/API

  • Connect via SSH: ssh pi@$RASPI_HOST -i $RASPI_SSH_KEY
  • Access configuration tool: sudo raspi-config (use options like "Boot Options" with flag --expand-rootfs for storage)
  • Control GPIO pins in Python: 
    import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BCM)
GPIO.setup(17, GPIO.OUT)
GPIO.output(17, GPIO.HIGH)
  • Update and install packages: sudo apt update && sudo apt install -y package-name (e.g., apache2 for a web server)
  • Check system status: vcgencmd measure_temp to get CPU temperature, or top for resource usage.
  • Config format for /boot/config.txt: Add lines like dtparam=i2c_arm=on to enable I2C, then reboot.

Integration Notes

When integrating with other systems, set auth variables in your environment, e.g., export RASPI_HOST=raspberrypi.local and export RASPI_SSH_KEY=/path/to/private.key. For API-like interactions, use SSH wrappers in scripts. Ensure network compatibility; if behind a firewall, forward ports like 22 for SSH. For IoT ecosystems, pair with MQTT brokers by installing mosquitto and configuring via /etc/mosquitto/mosquitto.conf with lines like listener 1883.

Error Handling

If SSH fails, verify connectivity with ping $RASPI_HOST and check key permissions (e.g., chmod 600 $RASPI_SSH_KEY). For GPIO errors, ensure RPi.GPIO is installed via pip install RPi.GPIO and handle exceptions like GPIO.error in code:

try:
    GPIO.setup(17, GPIO.OUT)
except RuntimeError as e:
    print("Error: " + str(e) + " - Check user permissions")

For apt issues, use apt --fix-broken install to resolve dependencies. Always log errors with timestamps, e.g., via echo "$(date): Error message" >> error.log.

Usage Examples

  1. Set up and blink an LED on GPIO pin 17: First, SSH in with ssh pi@$RASPI_HOST -i $RASPI_SSH_KEY, then create a script file with nano blink.py and add:

    import RPi.GPIO as GPIO
import time
GPIO.setmode(GPIO.BCM)
GPIO.setup(17, GPIO.OUT)
for _ in range(5):
    GPIO.output(17, True)
    time.sleep(1)
    GPIO.output(17, False)
    time.sleep(1)

    Run it with python blink.py to toggle the LED.

  2. Deploy a basic web server for IoT monitoring: SSH into the device, update packages with sudo apt update, install Apache via sudo apt install -y apache2, then edit the default page at /var/www/html/index.html by adding content like <h1>IoT Status: OK</h1>. Access it via http://$RASPI_HOST in a browser, and monitor logs with tail -f /var/log/apache2/access.log.

Graph Relationships

  • Related to cluster: iot
  • Connected skills: sensors (for GPIO integration), actuators (for hardware control), edge-computing (for resource monitoring)

FAQ

What does the raspberry-pi skill do?

Compact Linux board for IoT, prototyping, and edge computing

How do I install raspberry-pi?

Run npx skills add https://github.com/alphaonedev/openclaw-graph --skill raspberry-pi in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/raspberry-pi/ (personal) or .claude/skills/raspberry-pi/ (project).

Which AI agents can use raspberry-pi?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is raspberry-pi safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains raspberry-pi?

It is published by alphaonedev in alphaonedev/openclaw-graph. It has 98 recorded installs.

More from alphaonedev/openclaw-graph

View all →

playwright-scraper

alphaonedev/openclaw-graph

Playwright web scraping: dynamic content, auth flows, pagination, data extraction, screenshots

Testing & QA1.6K installs

humanize-ai-text

alphaonedev/openclaw-graph

Open the skill to read its SKILL.md instructions.

463 installs

gcp-iam

alphaonedev/openclaw-graph

Open the skill to read its SKILL.md instructions.

DevOps & Cloud431 installs

macos-automation

alphaonedev/openclaw-graph

Open the skill to read its SKILL.md instructions.

Productivity & Automation274 installs

food-order

alphaonedev/openclaw-graph

Open the skill to read its SKILL.md instructions.

249 installs

tavily-web-search

alphaonedev/openclaw-graph

Open the skill to read its SKILL.md instructions.

Productivity & Automation224 installs

Popular devops & cloud skills

View category →

microsoft-foundry

microsoft/azure-skills

Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure

OfficialDevOps & Cloud579.1K installs

azure-diagnostics

microsoft/azure-skills

Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.

OfficialDevOps & Cloud569.8K installs

azure-prepare

microsoft/azure-skills

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

OfficialDevOps & Cloud569K installs

azure-ai

microsoft/azure-skills

Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.

OfficialDevOps & Cloud568.8K installs

azure-deploy

microsoft/azure-skills

Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.

OfficialDevOps & Cloud568.6K installs

azure-validate

microsoft/azure-skills

Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.

OfficialDevOps & Cloud568K installs