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madhan-g-p/DevDocs-MCP

madhan-g-p/DevDocs-MCP

📇 🏠 🍎 🐧 - Version-pinned, offline documentation sourced from DevDocs.io
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add devdocs-mcp -- npx -y devdocs-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
13 ★ · madhan-g-p/DevDocs-MCP · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 13 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 madhan-g-p/DevDocs-MCP;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

DevDocs-MCP: Documentation Authority for AI Agents

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

> **Eliminate AI hallucinations with local, version-aware, and authoritative documentation.**
DevDocs-MCP is a Model Context Protocol (MCP) server that provides version-pinned, deterministic documentation sourced from DevDocs.io to AI assistants (Claude, RooCode, Cline, Copilot etc.). It acts as a local Documentation Intelligence Layer, ensuring your agent always has the correct API context without network latency or training data drift.
This server follows the proposed MCP server standard defined by the MCP , which is being adopted by AI tools and agents across the ecosystem, including those from providers such as Anthropic, OpenAI, and Google.
---
> ⚠️ **Project Status Notice** ⚠️
> This project is under active and heavy development. Still need to test existing features and implement more new features like optimal caching , update latest doc automatically and also on request basis , optimal querying and more... Design decisions, APIs, and structure are expected to evolve based on strong opinions, reviews, and feedback from the developer community. I warmly welcome discussions, critiques, and contributions to help shape this project in the right direction.
---
📑 Table of Contents
1. Overview
2. Key Capabilities
3. Quickstart
4. Installation & Setup
5. AI Agent Configuration
6. Further Reading
---
🎯 Overview
What This Project Is
- A **local MCP server** written in NestJS (TypeScript).
- A **deterministic authority** for documentation metadata and content.
- A **lazy-ingestion engine** that caches DevDocs offline.
- A **project-aware context manager** that pins docs to your package.json versions.
What This Project Is NOT
- ❌ An AI agent or code generator.
- ❌ A web scraper (it uses structured DevDocs datasets).
- ❌ A DevDocs UI replacement.
- ❌ A hosted SaaS (it runs 100% locally).
Why This Exists (The Problem)
Modern AI coding agents face three major hurdles:
1. **Hallucination**: Guessing API signatures or using deprecated methods.
2. **Latency**: Fetching live web docs for every query is slow.
3. **Version Drift**: Mixing up React 18 with React 19 features.
**The Solution**: DevDocs-MCP provides "Just-in-Time" documentation retrieved from local storage, filtered by your project's specific dependency versions.
Mental Model
DevDocs-MCP acts as a middleware between your IDE Agent and the documentation source.
---
🚀 Key Capabilities
- **Offline-First**: Documentation is cached locally; no internet is needed after ingestion.
- **Ranked Fuzzy Search**: Instantly find relevant entries (e.g., "intersection observer").
- **Version Awareness**: Automatically maps to specific library versions in your project.
- **Node-Only Architecture**: Uses sql.js for zero-native dependencies (no Python/C++ build steps).
- **Structured Outputs**: Returns clean, LLM-optimized content.
---
⚡ Quickstart
1. **Clone & Install**
2. **Configure Environment**
3. **Build & Run**
> **Note:** Strictly use pnpm for development and contributions.
---
🛠️ Installation & Setup
DevDocs-MCP is optimized for zero-fuss setup with pnpm. It is a **Node-only** project.
Prerequisites
- Node.js 18+ (tested on 18.x and 20.x).
🐳 Docker Usage
DevDocs-MCP is designed to be lightweight and persistent. Since it downloads and caches large documentation datasets, managing your data volumes correctly is essential.
来源
awesome · https://github.com/madhan-g-p/DevDocs-MCP
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