Sudoku MCP Server
A Cloudflare Worker-based MCP server for playing Sudoku, exposing five tools (start_game, get_game, play_move, check_game, reset_game) that let users start uniquely solvable puzzles, make moves, validate entries against a hidden solution, and reset games via a SQLite-backed Durable Object per game.
README
Sudoku MCP Server
A Cloudflare Worker exposing a small remote MCP server at /mcp. It implements
five gameplay tools: start_game, get_game, play_move, check_game, and
reset_game.
Local development
npm install
npm run types
npm test
npm run build
npm run dev
The root endpoint is a health response; MCP clients should use
http://localhost:8787/mcp.
Automatic deployment
.github/workflows/deploy.yml runs the tests and type-check on pull requests.
After a change reaches main, it deploys the Worker automatically. Configure
these GitHub Actions secrets before the first production deployment:
CLOUDFLARE_API_TOKEN: a Cloudflare API token permitted to deploy this Worker.CLOUDFLARE_ACCOUNT_ID: the Cloudflare account identifier for this Worker.
The token must be stored as a GitHub secret, never committed to the repository.
Authentication
Wrangler uses Cloudflare OAuth for local CLI operations:
npx wrangler login
npx wrangler whoami
This Worker intentionally has no application-level auth or user-account layer, as specified by the development plan. Add access control at the deployment boundary before exposing a production endpoint.
Game behavior
Puzzles are normalized to one 81-character row-major grid. Whitespace is
ignored, . and 0 mean empty, and digits 1-9 are givens. start_game
accepts only uniquely solvable puzzles and stores the solution privately inside
one SQLite-backed Durable Object per game ID. play_move enforces only visible
row/column/box conflicts; check_game is the tool that evaluates entries
against the hidden solution. Every state response includes the canonical
initial/current grids and a labeled board rendering.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。