开发者多功能工具 MCP 服务器

DevKnife 是一款零成本、高速的 MCP 服务器,为 AI 智能体提供 JSON 格式化、Base64 编解码、UUID 生成、哈希计算、正则测试、JWT 解码、Cron 解析、Markdown 转 HTML 等 15 多种开发工具,适用于需要在开发流程中精确处理数据的场景。

  • by cfunkycreations-tech
  • Python
  • 混合部署
  • 更新于
在 GitHub 查看 cfunkycreations-tech/devknife-mcp-server

使用说明

🛠️ DevKnife MCP Server

The Developer Swiss Army Knife for AI Agents.

DevKnife is a blazing-fast, zero-cost Model Context Protocol (MCP) server that bundles 15+ essential developer utilities. It gives your AI agents (like Claude Desktop, LangChain, or custom LLM apps) the ability to instantly validate, encode, decode, parse, and manipulate data without hallucinating.

🧰 Included Tools

  1. json_format: Format and validate JSON strings.
  2. base64_encode: Encode text to Base64.
  3. base64_decode: Decode Base64 strings.
  4. uuid_generate: Generate random UUID v4s.
  5. hash_compute: Compute MD5, SHA-1, SHA-256, or SHA-512 hashes.
  6. regex_test: Test regular expressions against strings and extract capture groups.
  7. jwt_decode: Decode JWT headers and payloads (no secret required).
  8. cron_parse: Parse cron expressions and get the next 5 occurrences.
  9. timestamp_convert: Convert between epoch timestamps and ISO 8601 strings.
  10. markdown_to_html: Convert Markdown to HTML.
  11. url_encode: URL encode a string.
  12. url_decode: URL decode a string.
  13. html_encode: Encode HTML entities.
  14. html_decode: Decode HTML entities.
  15. lorem_ipsum: Generate dummy text for testing.

🚀 Getting Started Locally

  1. Clone the repository:
    git clone https://github.com/yourusername/devknife-mcp.git
    cd devknife-mcp
    
  2. Install dependencies:
    npm install
    
  3. Start the development server (includes a UI playground):
    npm run dev
    
  4. The MCP SSE endpoint will be available at: http://localhost:3000/mcp/sse

☁️ Deployment Guide

This project is designed to be hosted for $0/month.

Option A: Render.com (Recommended)

Because the official @modelcontextprotocol/sdk relies on Node.js streams for Server-Sent Events (SSE), deploying to a native Node environment is highly recommended.

  1. Go to Render.com and create a New Web Service.
  2. Connect this GitHub repository.
  3. Build Command: npm run build
  4. Start Command: npm start
  5. Render will automatically provision a free URL (e.g., https://devknife-mcp.onrender.com/mcp/sse).

Option B: Cloudflare Workers

This repository includes a worker.ts and wrangler.toml for Edge deployment.

  1. Go to the Cloudflare Dashboard -> Workers & Pages.
  2. Click Create Application -> Pages -> Connect to Git.
  3. Select this repository.
  4. Framework preset: None
  5. Build command: npm install
  6. Note: Running the official MCP SDK on Cloudflare Workers currently requires bridging Web Streams to Node streams. If your MCP client fails to connect via Cloudflare, use Render.com instead.

🔌 Connecting to an MCP Client

DevKnife exposes an SSE (Server-Sent Events) transport.

If you are using an MCP client that supports SSE (like many web-based AI agents), simply provide your deployed URL: https://your-deployed-app.com/mcp/sse

(Note: Claude Desktop currently natively supports stdio transports. To use an SSE server with Claude Desktop, you may need a lightweight stdio-to-sse bridge script).