MCP server

Code Explainer

io.github.lazymac2x/code-explainer

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Cloudflare Workers MCP server: code-explainer

Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

6

Token cost

About 660 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http code-explainer https://api.lazy-mac.com/code-explainer/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.code-explainer]
url = "https://api.lazy-mac.com/code-explainer/mcp"

Gemini CLI

{"mcpServers":{"code-explainer":{"httpUrl":"https://api.lazy-mac.com/code-explainer/mcp"}}}

Cursor

{"mcpServers":{"code-explainer":{"url":"https://api.lazy-mac.com/code-explainer/mcp"}}}

VS Code

{"servers":{"code-explainer":{"type":"http","url":"https://api.lazy-mac.com/code-explainer/mcp"}}}

Antigravity

agy mcp add code-explainer https://api.lazy-mac.com/code-explainer/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"code-explainer","server_url":"https://api.lazy-mac.com/code-explainer/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"code-explainer","server_url":"https://api.lazy-mac.com/code-explainer/mcp"}

Tools

• analyze_all ~124 tokens
  Run all five analyses in one call: language detection, natural-language explanation, docstring generation, complexity metrics, and refactoring suggestions.
• analyze_complexity ~116 tokens
  Analyze code complexity including cyclomatic complexity, cognitive complexity, nesting depth, and maintainability index.
• detect_language ~81 tokens
  Detect the programming language of a code snippet. Returns the detected language and confidence level.
• explain_code ~112 tokens
  Generate a natural language explanation of a code snippet including structural analysis, features, and summary.
• generate_docstring ~117 tokens
  Generate JSDoc, Python docstring, Go godoc, or Rust doc comments for functions in the provided code.
• suggest_refactor ~110 tokens
  Get prioritized refactoring suggestions for code quality improvements.

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