Yahboom Mcp

io.github.sandraschi由 GitHub 帳號 sandraschi 發布v2.5.0b1更新於 Oct 27, 2026

SOTA 2026 Yahboom Raspbot v2 ROS 2 MCP Server

概覽

AI 產生的概覽

讓 AI 助理透過 ROS 2 控制 Yahboom Raspbot v2(Boomy)機器人小車的 MCP 伺服器,可執行任務、讀取遙測與診斷。

可以做什麼
  • 控制機器人:透過 MCP 工具與通用工具操作驅動麥輪底盤、燈條、OLED 等周邊裝置。
  • 執行代理任務:把自然語言目標轉成計畫並在機器人上執行,含視覺偵測與超音波避障。
  • 檢查執行堆疊:瀏覽 ROS 主題與節點、查看堆疊健康狀態、讀取日誌並進行以 SSH 為基礎的診斷。
  • 搭配網頁儀表板進行人工遙測觀察與周邊控制,與機器介面並存。
適用情境
適合已擁有 Yahboom Raspbot v2、希望讓 AI 代理駕駛機器人、執行規劃任務,或從桌面 MCP 用戶端檢查其 ROS 2 執行堆疊與健康狀態的使用者。
執行需求
以 stdio 方式在本機執行;README 提供透過 uvx 從 Git 儲存庫安裝、Claude Desktop 的 MCPB 套件,以及 Windows 安裝程式。需要能連上機器人網路,以 YAHBOOM_IP 環境變數設定,並具備可用的 ROS 2 / rosbridge 或 ESP32 連線。選用的 LLM 規劃使用 Ollama、LM Studio 或 Gemini。
安裝前請注意
Windows 安裝程式未簽章,SmartScreen 會提出警告。伺服器可驅動實體機器人並執行自主任務,需確保周遭環境安全並有人監督。它可建立 SSH 工作階段並讀取容器日誌,也會透過網路連線機器人及已設定的 LLM 供應商。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Yahboom Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

Yahboom Raspbot v2 (Boomy) — MCP Server, Webapp & Documentation

[Just] [Ruff] [Python] [Biome] [FastMCP]

📖 Installation Guide — quick start, manual setup, and troubleshooting

[CI] [FastMCP 3.4] [Python 3.12+] [ROS 2 Humble] [Ruff] [Biome] [License] [Stars] [Last commit] [Ollama] [LM Studio] [Topics]

[Boomy Hero Shot]

Download for Windows: yahboom-mcp-2.5.0-setup.exe — installer with webapp + embedded backend, one shortcut. The installer is unsigned: SmartScreen will warn — click More info > Run anyway. Claude Desktop users can instead install the MCP bundle (one-liner below).

Quick Start

Claude Desktop only (MCPB bundle):

powershell
irm https://github.com/sandraschi/yahboom-mcp/releases/latest/download/install.ps1 | iex

Every other client (Cursor, Windsurf, OpenCode, Claude Code) — stdio via uvx:

json
{  "mcpServers": {    "yahboom-mcp": {      "command": "uvx",      "args": ["--from", "git+https://github.com/sandraschi/yahboom-mcp", "yahboom-mcp", "--mode", "stdio"],      "env": { "YAHBOOM_IP": "192.168.1.11" }    }  }}

Developers from source:

powershell
git clone https://github.com/sandraschi/yahboom-mcpcd yahboom-mcpjust

This opens an interactive dashboard showing all available commands. Run just bootstrap to install dependencies, then just serve or just dev to start.

Manual Setup

If you don't have just installed:

Overview

Boomy is a Yahboom Raspbot v2 (Mecanum Version) robot car. Weighing in at approximately 1.0 kg and costing roughly $300 (fully loaded with a Raspberry Pi 5 16GB), it provides a unified platform for testing sensor integration, ROS 2 orchestration, and agentic (AI-driven) robotics. It's also great fun for kids of all ages.

The Manufacturer: Yahboom

Yahboom is a prominent player in the Chinese robotics and STEM education industry. They offer a diverse range of hardware platforms:

  • Market Range: From entry-level $50 DIY kits to advanced $2,000+ STEM robots with precision mechanical arms.
  • Industry Position: They specialize in accessible hardware for education and prototyping, positioned below enterprise-grade platforms such as Unitree or Noetix.
  • Developer Ecosystem: Yahboom maintains a strong commitment to a FOSS (Free and Open Source Software) stack and provides active GitHub support for developers.

🏗️ Hardware Architecture

Boomy utilizes a "Double-Stack" controller model to bridge real-time physical reliability with high-level cognitive tasks:

  1. Rosmaster (ESP32 / Micro-ROS): Small-form-factor hardware controller for low-latency motor control, ultrasonic pinging, and line-sensor processing.
  2. Raspberry Pi 5 (Optional / Gateway): The main brain for standalone operation.

🚀 The "Zero-Host" Swarm Config

For scaled deployments, Boomy can operate in a Pi-less Swarm mode:

  • Setup: Remove the Raspberry Pi; replace with a WiFi-to-Ethernet/UART bridge ($15).
  • Control: Centralized orchestration via a remote Mothership (PC with RTX 4090).
  • Scaling: Deploy 3+ units for the price of a single Pi-hosted robot.

🕹️ Interface Separation

This project clearly distinguishes between human-operable controls and machine-optimized interfaces:

  • Human Interface: A browser-based Web Dashboard (React/Vite) designed for manual telemetry observation, peripheral control (lights, OLED), and human-robot interaction.
  • Machine Interface: A standards-compliant MCP Server (Model Context Protocol) designed for AI agents and MCP clients to programmatic control Boomy as a tool within a larger fleet.

Fleet Crossconnects (Companions)

yahboom-mcp works completely standalone. You can optionally connect it with companion servers in the sandraschi fleet to unlock extended features:

Companion ServerFeature UnlockedStatusSetup
speech-mcpspoken-feedback, voice-synthesisOptionalInstall Guide
reaper-mcpaudio-playback, soundboard-fxOptionalInstall Guide
virtualdj-mcpdeck-control, music-playbackOptionalInstall Guide

Self-Contained Companions: Fleet companions operate independently. Installing companions does not trigger transitive dependency chains.


📂 Documentation Pillars

PillarFocusKey Topics
Autonomous Missionsv2.4.0 — Ollama → ROSNatural-language goals → LLM planning → ROS execution; vision detection (SSD MobileNet v2); ultrasonic obstacle avoidance; "find our dog" walkthrough.
Startup & bringupStart here (robot + Goliath)ROS 2 vs rosbridge_suite (software) vs USB controller tier under the Pi; boot order; Docker/systemd on the Pi; what the webapp can restart; dashboard vs diagnostics.
Agent missions & MCPLLM → Pi missionsyahboom_agent_mission (MCP) and POST /api/v1/agent/mission (HTTP); MissionPlanV1; env vars; boomy_mission_executor; Nav2 and /boomy/detections_json; troubleshooting vs yahboom_agentic_workflow.
Rosmaster ArchitectureDual-bus analysisI2C (0x2b) for motors/sensors, UART for IMU/battery; register map; container layout; micro-ROS analysis.
Stack health probehealth.stackTTL SSH/TCP probes, YAHBOOM_ROS2_CONTAINER, lifecycle (never started vs exited vs restart loop), optional docker logs preview (redacted).
Setup & InstallationDev installuv, modes, baseline env vars.
Software & LogicArchitectureSystem design, ROS 2 node graphs, and state management.
Hardware & PinoutsPhysical LayerWiring diagrams, I2C addresses, and sensor technical specs.
Raspbot v2 hardware stackBoomy chassisChassis, mecanum, motors, lightstrip, PTZ, camera, IMU, ultrasonic, line/cliff, expansion board vs rosbridge software, Pi ports, I2C, battery, switch.
ROS 2 BridgeConnectivityBridge architecture, topic map, state cache, env vars, known bugs.
Voice & AudioSound SystemCSK4002 module protocol, espeak-ng TTS, chatrobot architecture, audio soundboard with 17 built-in effects.
Multi-Robot IntegrationEcosystemFederated fleet standards and cross-robot communication protocols.
ConfigurationReferenceEnv vars, ports, transport modes, LLM providers.
DevelopmentReferenceDev setup, layout, test commands, five-gate.
ToolsReferenceMCP tools, yahboom_tool operations, REST endpoints.
TroubleshootingReferenceCommon issues and fixes.
OnboardingFirst-time setupHardware bring-up for Boomy (robot power, IP, sanity checks).

Webapp status surfaces

  • Dashboard (/dashboard) — First page: basic robot link (gateway, target IP, ROS · SSH · video) and operator hints when the Raspbot is off or Goliath has no AP/Ethernet path.
  • Diagnostic Hub (/diagnostics) — Detail: ROS topic explorer, node list, resync / hard reset, SSH shell, stack health table (same stack payload as the dashboard when available).
  • Server logs (/logs) — Live yahboom-mcp log stream (SSE) on Goliath.

Historical status logs and legacy research are preserved in the docs/archive/ directory.

Stack

LayerTech
MCPFastMCP 3.4 (Unified Gateway: stdio + HTTP/SSE)
BackendFastAPI + uvicorn, Pydantic v2, structlog
Robot linkroslibpy (rosbridge) / direct ESP32 TCP / mock bridge, paramiko SSH
Vision/audioOpenCV, faster-whisper, edge-tts, pytapo
FrontendReact 19 + Vite 5 + TailwindCSS 3 + Lucide + Framer Motion + Zustand + Three.js
Package managersuv (Python), bun (webapp)
DesktopTauri 2 + NSIS (PyInstaller sidecar backend)
Qualityruff + pyright + pytest (+coverage) / tsc + Biome / Playwright
LLMOllama (:11434) + LM Studio (:1234) auto-discovery, Gemini mission planning

🛡️ Industrial Quality Stack

This project adheres to SOTA 2026 industrial standards for high-fidelity agentic orchestration:

  • Python (Core): Ruff for linting and formatting. Zero-tolerance for print statements in core handlers (T201).
  • Webapp (UI): Biome for sub-millisecond linting.
  • MCP: FastMCP 3.4 with Unified Gateway, portmanteau tools, skills, and agentic sampling.
  • LLM Providers: Auto-discovery of Ollama (:11434) and LM Studio (:1234). GPU metrics via nvidia-smi.
  • Automation: Justfile recipes for all fleet operations (just lint, just fix, just dev).

來源:README.md,提交 58378e3

工具

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版本歷史

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  1. v2.5.0b1最新Sep 16, 2026

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