mcpField
C
Code Explainer MCP

Code Explainer MCP

Local
github.com/BillDuke13Developer Tools8Updated 22w ago

About Code Explainer MCP

Code Explainer MCP is a Cloudflare Worker that turns source snippets into Markdown reports with an architecture diagram, functionality summary, and component descriptions. It uses pattern matching rather than LLM calls; despite its name, it currently provides a regular HTTP JSON API, not an MCP protocol endpoint.

Key features

  1. 01Generate ASCII architecture diagrams
  2. 02Summarize core code functionality
  3. 03Describe main classes and functions
  4. 04Support several languages and reuse comments
  5. 05Protect the endpoint with bearer-token auth

Use cases

  1. 01Map the structure of unfamiliar code
  2. 02Review a code snippet's purpose and components
  3. 03Generate a code analysis report through HTTP

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Code Explainer MCP

A Cloudflare Worker that explains source code. Given a snippet and its language, it returns a Markdown report containing an ASCII architecture diagram, a core-functionality summary, and a breakdown of the main classes and functions.

License

Analysis runs entirely inside the Worker using regex and pattern matching — there are no LLM calls and no external runtime dependencies. All logic lives in a single file, src/index.ts.

Features

  • Architecture diagram: Generates an ASCII diagram showing classes (with inheritance), standalone functions, call relationships, and imported dependencies.
  • Core-functionality analysis: Infers the primary and secondary purpose of the code (network, UI, data processing, database, authentication, testing, algorithm, file system) from weighted pattern matches.
  • Component breakdown: Lists the main classes and functions, each with a short generated description.
  • Multi-language support: Tailored class/function/import patterns for JavaScript, TypeScript, Python, Java, and C#, with a generic fallback for other languages.
  • Documentation extraction: Reuses existing JSDoc, Python docstrings, and line comments when describing a component.
  • Bearer-token auth: The POST endpoint is protected by a shared secret.

How it works

explainCode(code, language) orchestrates four helpers and assembles their output into a Markdown report:

  1. generateArchitectureDiagram — extracts classes, functions, and imports with language-specific regexes and renders an ASCII diagram, including inherits/calls relationships.
  2. extractCoreFunctionality — counts matches across purpose categories and produces a prose summary of the primary (and secondary) purpose.
  3. extractComponents — collects the main classes and functions; extractBlock finds each declaration's body by brace matching (or by indentation for Python).
  4. generateComponentDescription — prefers an existing doc comment for each component and otherwise infers a description from code patterns.
A note on "MCP"

The project is named for the Model Context Protocol and keeps workers-mcp in its deploy pipeline (workers-mcp docgen runs before wrangler deploy). However, the current src/index.ts does not use workers-mcp at runtime and does not implement the MCP JSON-RPC wire protocol. It serves a plain HTTP JSON endpoint with a custom { method, params } body, handled directly by the Worker's default fetch export. Clients call it as a regular HTTP API (see Usage).

Prerequisites

  • Node.js 22 or higher
  • Wrangler (installed locally via devDependencies)
  • A Cloudflare account (for deployment)

Setup

  1. Clone the repository:

    git clone https://github.com/BillDuke13/code-explainer-mcp.git
    cd code-explainer-mcp
    
  2. Install dependencies:

    npm install
    
  3. Configure the shared secret. For production, store it as a Worker secret (recommended):

    wrangler secret put SHARED_SECRET
    

    The vars.SHARED_SECRET entry in wrangler.jsonc is only the placeholder "YOUR_SECRET_KEY_HERE"; never commit a real secret there. The Worker fails closed — while the secret is unset or still the placeholder, every POST returns 503, so a real secret must be set before the endpoint will serve. For local development, put the secret in .dev.vars (gitignored) instead — see Local development.

  4. Deploy to Cloudflare Workers:

    npm run deploy
    

Usage

Endpoint

Send a POST request to your Worker URL with a JSON body:

{
	"method": "explainCode",
	"params": ["your code here", "programming language"]
}

Include the bearer token in the Authorization header:

Authorization: Bearer <SHARED_SECRET>

A GET request to the same URL returns a small HTML info page instead of running an analysis.

Response

On success the response is a JSON object whose result field holds the Markdown report:

{
	"result": "# Code Analysis for javascript Code\n\n## Architecture Diagram\n...\n\n## Core Functionality\n..."
}
Status codes
StatusWhenBody
200Valid POST, or a GET/HEAD{ "result": "<markdown>" } / HTML
401POST with a missing or incorrect Authorization headerUnauthorized
503SHARED_SECRET is unset or still the placeholder (the Worker fails closed)Service not configured: …
400method is not explainCode, fewer than two params, or non-string paramsInvalid method or parameters
413The code (params[0]) exceeds the maximum length (100,000 characters)Code exceeds the maximum length …
405A request method other than POST, GET, or HEADMethod Not Allowed
500Request body is not valid JSON, or another error occursError processing request
Examples
JavaScript (browser)
async function explainCode(code, language) {
	const response = await fetch('https://your-worker-url.workers.dev', {
		method: 'POST',
		headers: {
			'Content-Type': 'application/json',
			Authorization: 'Bearer YOUR_SECRET_KEY_HERE',
		},
		body: JSON.stringify({
			method: 'explainCode',
			params: [code, language],
		}),
	});

	if (!response.ok) {
		throw new Error(`HTTP error! status: ${response.status}`);
	}

	const data = await response.json();
	return data.result;
}

const jsCode = `function add(a, b) { return a + b; }`;
explainCode(jsCode, 'javascript')
	.then((explanation) => console.log(explanation))
	.catch((error) => console.error('Error:', error));
Python (requests)
import requests


def explain_code(code, language, api_url, secret_key):
    headers = {
        'Content-Type': 'application/json',
        'Authorization': f'Bearer {secret_key}',
    }
    payload = {
        'method': 'explainCode',
        'params': [code, language],
    }
    response = requests.post(api_url, headers=headers, json=payload)
    response.raise_for_status()
    return response.json()['result']


code = "def hello():\n    print('Hello, world!')"
explanation = explain_code(code, 'python', 'https://your-worker-url.workers.dev', 'YOUR_SECRET_KEY_HERE')
print(explanation)
Node.js (axios)
const axios = require('axios');

async function explainCode(code, language) {
	const response = await axios.post(
		'https://your-worker-url.workers.dev',
		{ method: 'explainCode', params: [code, language] },
		{
			headers: {
				'Content-Type': 'application/json',
				Authorization: 'Bearer YOUR_SECRET_KEY_HERE',
			},
		},
	);
	return response.data.result;
}

Local development

  1. Install dependencies (npm install) if you have not already.

  2. Provide the local secret. Create a .dev.vars file (gitignored) so wrangler dev injects it:

    SHARED_SECRET=your-local-secret
    

    The Worker fails closed, so .dev.vars must hold a real secret: with the wrangler.jsonc placeholder (or no secret at all), every POST returns 503.

  3. Start the dev server (http://localhost:8787):

    npm run dev
    
  4. Send a request:

    curl -X POST http://localhost:8787 \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer your-local-secret" \
      -d '{"method":"explainCode","params":["function hello() { return \"Hello World\"; }","javascript"]}'
    
Quality checks
  • Tests (Vitest on @cloudflare/vitest-pool-workers): npm test. The suite in test/ drives the Worker through SELF.fetch, covering the GET info page, auth failures, the explainCode contract for JavaScript and Python, empty input, and request validation.
  • Lint (ESLint flat config): npm run lint, or npm run lint:fix to auto-fix.
  • Type-check: npx tsc --noEmit checks src/. The root tsconfig.json excludes test/, so type-check the tests separately with npx tsc -p test/tsconfig.json --noEmit.
  • Regenerate binding types: after changing bindings or vars in wrangler.jsonc, run npm run cf-typegen to rewrite worker-configuration.d.ts.

Formatting is owned by Prettier (.prettierrc: tabs, single quotes, semicolons, printWidth 140) — run npx prettier --write ..

Project layout

src/index.ts        Worker entry point and all analysis logic
test/index.spec.ts  Vitest suite exercising the HTTP contract
docs/index.html     Browsable HTML documentation
wrangler.jsonc      Worker configuration

Documentation

Detailed, browsable documentation lives in docs/index.html — open it in a browser for the architecture overview, the analysis pipeline, the full API reference, and known limitations.

Security

  • The POST endpoint is protected by Authorization: Bearer <SHARED_SECRET>.
  • The Worker fails closed: it returns 503 until SHARED_SECRET is set to a real value (not the placeholder), so a misconfigured deploy refuses requests instead of accepting the public default.
  • Store the secret with wrangler secret put SHARED_SECRET for production and in .dev.vars for local development; never commit a real value to wrangler.jsonc.
  • The token is checked by comparing SHA-256 digests in constant time, leaking neither the secret's content nor its length through response timing. For higher-assurance deployments, add rate limiting in front of the Worker.
  • Request size is bounded: oversized bodies are rejected with 413 (via Content-Length), and code longer than 100,000 characters is rejected before any analysis runs.

License

This project is licensed under the Apache License 2.0 — see the LICENSE file for details.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.