What does Penqwin do differently from full file loading?
It sends structural skeletons (imports, exports, signatures, JSDoc) instead of full source code, reducing token context by 80–95%.
@sarinmsari
基本信息
An AST-based Model Context Protocol (MCP) server that provides token-efficient codebase skeletons to LLM agents (like Cursor, Claude Desktop, and Antigravity).
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"penqwin": {
"command": "npx",
"args": [
"-y",
"@penqwin/mcp"
],
"env": {
"PENQWIN_API_KEY": "YOUR PENQWIN API KEY",
"PENQWIN_ORG_ID": "YOUR PENQWIN ORG ID",
"PENQWIN_REPO": "YOUR GITHUB REPO URL",
"PENQWIN_API_URL": "https://app.penqwin.com"
}
}
}
}Returns a compact table-of-contents for the repository 'YOUR GITHUB REPO URL'. Lists all tracked source files with their exported symbol names. ALWAYS call this FIRST before any other tool to understand the repository structure. Use the file paths returned here as input to get_folder_skeleton or get_file_skeleton. Cost: ~10-20 tokens per file — very cheap.
Returns compact AST skeletons for all source files under a given folder path prefix. Use this to understand a module or feature area without reading raw source files. Skeletons include: exports, function signatures, type definitions, and doc comments. Cost: ~50 tokens per file — much cheaper than raw source code. Tip: call get_repo_index first to discover valid folder paths.
Returns the AST skeleton for a single specific source file. The skeleton includes: all exports with signatures, imports, class members, and doc comments. Use this when you need the details of one specific file after narrowing down from get_repo_index. For multiple related files, prefer get_folder_skeleton — it is one round trip.
Searches the entire repository for files that export a specific symbol name. Use this to find where a function, class, type, or interface is defined. Returns: file path, language, kind (function/class/type/etc.), signature, and doc comment. Example: search for 'createClient' to find all files that export a function by that name.
Returns aggregate statistics for the repository 'YOUR GITHUB REPO URL'. Includes: total file count and a breakdown by programming language. Use this to understand the tech stack and scale of the codebase at a glance.
An AST-based Model Context Protocol (MCP) server that provides token-efficient codebase skeletons (imports, exports, signatures, JSDoc comments) to LLM agents like Cursor, Claude Desktop, and Antigravity. It reduces token context sizes by 80% to 95% during codebase exploration and navigation.
Install via npm install @penqwin/mcp and build with npm run build. Configure environment variables (PENQWIN_API_KEY, PENQWIN_ORG_ID, PENQWIN_REPO, PENQWIN_API_URL) and integrate with your IDE using npx or by pointing to the local build. Run node dist/index.js to start the stdio server.
get_repo_index, get_folder_skeleton, get_file_skeleton, search_symbols, get_repo_stats.eng-doc backend server.It sends structural skeletons (imports, exports, signatures, JSDoc) instead of full source code, reducing token context by 80–95%.
Node.js v18+ and an active eng-doc backend server with a valid API key generated from the eng-doc platform.
Set environment variables `PENQWIN_API_KEY`, `PENQWIN_ORG_ID`, `PENQWIN_REPO`, and `PENQWIN_API_URL`.
It uses stdio transport for MCP integration.
Cursor, Claude Desktop, and Antigravity/Gemini Code Assistant.

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