Dotfiles MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Dotfiles MCP ServerGenerate my bi-weekly report from GitHub PRs"
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.
Dotfiles MCP Server
這是一個 MCP (Model Context Protocol) 伺服器,讓大型語言模型 (LLMs) 如 Claude 或 Copilot 可以存取並執行您的自動化腳本。 此專案旨在讓使用者無需完整複製龐大的 dotfiles 儲存庫,也能透過簡單的設定流程,快速使用這些強大的開發工具。
功能
自動化工具整合:自動將
bin/目錄下的 Shell 腳本轉換為可供 LLM 呼叫的 MCP 工具。便攜式設計:內建設定腳本,自動下載所需腳本並設定環境,隨裝隨用。
安全路徑管理:支援動態路徑配置,確保工具在正確的環境下執行。
Related MCP server: TermPipe MCP
包含的工具腳本
安裝後,LLM 將能夠使用以下工具:
bi-weekly-report: 自動生成雙週工作報告 (透過 GitHub PRs)checkout-ticket: 根據 JIRA 票號快速建立並切換開發分支checkout-config: 快速切換設定檔專案分支deploy-console: 觸發 Jenkins 部署 Console 專案deploy-one: 觸發 Monorepo 部署trace-build: 追蹤 Jenkins 建置狀態並回報進度review-ticket: 協助進行 Code Review
快速開始
1. 複製專案
git clone https://github.com/andrew-wu-12/dotfile-mcp-server.git
cd dotfile-mcp-server2. 執行自動化設定
此指令會自動下載最新的腳本、安裝 NPM 相依套件,並編譯 TypeScript 程式碼。
npm run setup3. 設定 MCP 客戶端
設定腳本執行完畢後,會直接在終端機顯示您需要的設定資訊。請根據您使用的客戶端進行設定。
Claude Desktop / OpenCode 設定
將以下 JSON 設定加入您的設定檔 (例如 claude_desktop_config.json 或 opencode.json):
{
"mcpServers": {
"dotfiles": {
"command": "node",
"args": ["{dotfile-mcp-server 絕對路徑}/dist/index.js"],
"env": {
"DOTFILES_PATH": "{dotfile-mcp-server 絕對路徑}"
}
}
}
}Claude Code (CLI) 使用方式
若要在 Claude Code CLI 中直接加入此伺服器,請執行以下指令(npm run setup 結束時會提供包含正確路徑的完整指令):
claude mcp add dotfiles -- /usr/bin/env DOTFILES_PATH="{dotfile-mcp-server 絕對路徑}" node "{dotfile-mcp-server 絕對路徑}/dist/index.js"開發與維護
更新腳本: 重新執行
npm run setup即可重新下載最新的腳本。重新建置:
npm run build
授權
ISC
Available Tools
1 toolread_fileD
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Relative path to the file in the dotfiles repo |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
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.
1 tool update
v1.0.0- First observed
read_file
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion between tools. The tool name 'read_file' is clear and unambiguous.
Single tool means no inconsistency. The verb_noun pattern is followed.
A single 'read_file' tool is insufficient for a dotfiles server, which typically requires at least listing and writing capabilities.
The tool surface is severely incomplete for managing dotfiles. Only reading is possible; no listing, writing, or other operations are present.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Operate Linux, macOS and Windows from your LLM. Every action runs through an auditable allowlist.
- mcp-serverOAuthcom.make
Give your AI agents the tools to build, manage, and run automation workflows.
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Git-backed platform for skills, tools, and context for AI agents
Related MCP Servers
- FlicenseBqualityDmaintenanceEnables AI assistants to interact with GitHub repositories, Confluence documentation, and Databricks Unity Catalog through comprehensive tools for code exploration, documentation retrieval, and data schema management.19-
- AlicenseNot gradedqualityDmaintenanceProvides AI assistants with direct terminal access to execute commands, manage files, and run persistent REPL sessions. It features automated installation scripts that educate AI assistants on its capabilities for seamless integration.MIT
- AlicenseBqualityDmaintenanceEnables Git repository interaction and automation via LLMs, providing tools to read, search, and manipulate Git repositories.15164MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to manage dotfiles using git bare repos, supporting tracking, syncing, multiple stores, and remote setup through natural language.MIT