Does Code Explainer MCP use an LLM?
No. All analysis is done with regex and pattern matching inside the Worker, with no LLM calls and no external runtime dependencies.
@BillDuke13
基本信息
A Cloudflare Worker that serves as an MCP (Model Context Protocol) server for code explanation. It analyzes and explains code with a comprehensive breakdown of structure and functionality.
工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Code Explainer MCP is a Cloudflare Worker that analyzes source code snippets and returns a Markdown report containing an ASCII architecture diagram, a core-functionality summary, and a breakdown of main classes and functions. It uses only regex and pattern matching—no LLM calls or external dependencies—and supports JavaScript, TypeScript, Python, Java, and C# with a generic fallback.
Deploy the Worker to Cloudflare, set the SHARED_SECRET secret, then send a POST request to the Worker URL with a JSON body containing "method": "explainCode" and "params": [code, language]. Include the bearer token in the Authorization: Bearer <SHARED_SECRET> header. For local development, run npm run dev after setting the secret in .dev.vars.
No. All analysis is done with regex and pattern matching inside the Worker, with no LLM calls and no external runtime dependencies.
The code string (`params[0]`) must not exceed 100,000 characters; longer input is rejected with a `413` status.
No. Despite its name, the current version serves a plain HTTP JSON endpoint with a custom `{ method, params }` body. It does not use `workers-mcp` at runtime or implement JSON-RPC.
The POST endpoint is protected by a bearer token (`SHARED_SECRET`) sent in the `Authorization` header. The Worker fails closed—returning `503` if the secret is unset or still the placeholder—and compares digests in constant time.
Node.js 22 or higher, Wrangler (included in devDependencies), and a Cloudflare account. The Worker is deployed to Cloudflare Workers and tested with Vitest and `@cloudflare/vitest-pool-workers`.
Query your team's drift, vulnerability, and migration data from any AI assistant. Vibgrate MCP connects Cursor, Claude, ChatGPT, Windsurf, or VS Code to Vibgrate Cloud: 51 tools for DriftScores, CVEs and EOL runtimes, up

The tools your AI needs to make your games. Turn prompts into production-ready game assets — animated characters with their weapons attached, seamless textures, terrain, VFX, HUDs — and playable game kits Unity, Godot, U

The BetterBugs MCP (Model Context Protocol) enables you to load BetterBugs bug reports (via report links) directly to your preferred AI Agents and developer environments with MCP Client capabilities (such as Cursor, VS C

MCP server for AI Agents — exposes Yocoolab feedback threads and design selections as tools

评论