Mo5 Mcp Server

io.github.thlg057由 GitHub 帳號 thlg057 發布v1.0.2更新於 Oct 24, 2026

MCP server for Thomson MO5 C development, 6809, CMOC, SDK, toolchain.

已驗證STDIO僅桌面知識與記憶開發者工具

概覽

AI 產生的概覽

一個本機 MCP 伺服器,將 AI 助理連接到 MO5 RAG 知識庫與 Thomson MO5 6809 開發建置工具。

可以做什麼
透過 RAG 伺服器對 MO5 技術文件進行語意搜尋,並瀏覽已索引文件、標籤與索引狀態。啟用預先設定的 Thomson MO5 專家提示,用於開發問答。產生可開機的 .fd 磁碟映像,將 .fd 映像轉換為 SDDrive 用的 .sd,並把 PNG 素材轉換為 C 精靈標頭檔。
適用情境
適合使用 CMOC 與 6809 為 Thomson MO5 微型電腦開發軟體時使用,也適合讓助理依據精選文件庫回答 MO5 技術問題並產生磁碟映像或精靈標頭檔。
執行需求
透過 npx 或原始碼在本機執行,需要 Node.js v18 或更高版本。必須設定環境變數 RAG_BASE_URL 指向 MO5 RAG 伺服器;有提供公用執行個體,自架為選項。僅 PNG 轉精靈工具需要 Python 3 與 Pillow。需要能連線至 RAG 伺服器的網路。
安裝前請注意
伺服器會將查詢傳送到 RAG_BASE_URL 指定的 RAG 伺服器,因此文件內容與問題會離開本機;只應指向你信任的執行個體。建置工具會在本機寫入磁碟映像與 C 標頭檔等檔案。PNG 轉精靈工具依賴另行安裝的 Python 套件。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Mo5 Mcp Server,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

MO5 MCP Server (RAG Connector)

This MCP server (Model Context Protocol) acts as a bridge between modern AI agents (Claude Desktop, Augment, Cursor) and the Thomson MO5 ecosystem.
It allows access to an expert knowledge base and manipulation of MO5 heritage files.

It provides semantic search tools, documentation resources, and expert prompts to facilitate development around the Thomson MO5 microcomputer.

🏗️ MO5 Development Ecosystem

This server is part of a complete toolchain for modern 6809 development:

🌐 RAG Infrastructure (Artificial Intelligence)

The server relies on a Retrieval-Augmented Generation architecture to provide accurate answers based on real technical documentation.

🚀 Features

  • Semantic Search: Intelligent search within the MO5 technical documentation.
  • Resources Explorer: Direct access to the list of documents, tags, and indexing status.
  • Expert Prompt: A preconfigured "Expert Thomson MO5" mode for the AI.
  • Build Tools: Generate bootable .fd disk images, convert .fd to .sd for SDDrive, and convert PNG assets to C sprite headers.
  • Robustness: Native handling of timeouts (30s) and retry policy for unstable network environments (NAS).

🌐 Public MO5 RAG Server

The MO5 RAG server is now publicly deployed and accessible on the Internet.

👉 https://retrocomputing-ai.cloud/

This MCP server is designed to work out of the box with the public RAG instance.

For most users, this means:

  • no RAG server to install
  • no Docker setup
  • no local infrastructure to maintain

Simply configure the MCP server to point to the public URL and start using it from your coding agent.

Self-hosting a RAG server is still possible if you want to:

  • experiment with the internals
  • customize the knowledge base
  • run everything offline

But it is no longer required for normal usage.

🛠️ Requirements

  • Node.js (v18 or higher)
  • Python 3 with Pillow (pip install Pillow) — required only for the png_to_mo5_sprite tool.

The official public MO5 RAG server is available at: https://retrocomputing-ai.cloud/

You can use this public instance directly, there is no need to host your own RAG server.

📦 Installation & Setup

Option 1 — Via npx (recommended, no installation required)

Configure your agent to run the server directly from npm. No git clone or npm install needed.

json
{  "mcpServers": {    "mo5-server": {      "command": "npx",      "args": [        "-y",        "@thlg057/mo5-rag-mcp"      ],      "env": {        "RAG_BASE_URL": "https://retrocomputing-ai.cloud"      }    }  }}

Option 2 — From source

bash
git clone https://github.com/thlg057/mo5-mcp-server.gitcd mo5-mcp-servernpm install

Then configure your agent:

json
{  "mcpServers": {    "mo5-rag": {      "command": "node",      "args": ["C:\\your\\path\\to\\mo5-mcp-server\\index.js"],      "env": {        "RAG_BASE_URL": "https://retrocomputing-ai.cloud"      }    }  }}

Note for Windows: Use double backslashes \\ or single slashes / in the path to avoid JSON formatting errors.

🤖 Integration into an Agent (e.g., Augment, Claude Desktop)

Add one of the configurations above to your MCP configuration file (e.g., augment_config.json or claude_desktop_config.json).

🧪 Local Testing

It is recommended to test the server before integration to ensure proper communication with the RAG API.

Via the MCP Inspector (Recommended)

bash
# Windows (PowerShell)$env:RAG_BASE_URL="https://retrocomputing-ai.cloud"; npx @modelcontextprotocol/inspector node index.js

Via Command Line

bash
echo {"jsonrpc":"2.0","method":"tools/list","id":1} | node index.js

📂 Project Structure

  • index.js: Main source code of the MCP server.
  • scripts/: Python scripts for build tools (makefd.py, fd2sd.py, png2mo5.py).
  • package.json: Dependencies (MCP SDK).
  • .gitignore: Ignores node_modules and environment files.

🏗️ MO5 Development Ecosystem

This server is part of a suite of tools designed to modernize development on the Thomson MO5:

  • SDK MO5: A C library for CMOC that provides easy access to the hardware (video, keyboard, monitor) without writing assembly.
  • Project Template: A ready-to-use project skeleton with an automated Makefile that compiles, links the SDK, and generates a bootable disk image in a single command. Also includes this MCP server as a dev dependency so your coding agent has full context and build capabilities out of the box.

This project is part of the digital preservation ecosystem for the Thomson MO5 microcomputer.

來源:README.md,提交 e41c09c

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v1.0.2最新Sep 16, 2026

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