广告合作
MCP.so
登录

AWS Amplify Gen 2 Documentation MCP Server

@unirt

代码仓库

基本信息

分类

记忆与知识

传输方式

stdio

作者

unirt

关于 AWS Amplify Gen 2 Documentation MCP Server

This MCP server provides tools to access AWS Amplify Gen 2 documentation and search for content. (not official)

#aws#amplify#documentation#mcp-server

AWS Amplify Gen 2 Documentation MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "unirt.amplify-doc-mcp-server": {
      "command": "uvx",
      "args": [
        "unirt.amplify-doc-mcp-server@latest"
      ],
      "env": {
        "FASTMCP_LOG_LEVEL": "ERROR"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

AWS Amplify Gen 2 Documentation MCP Server 工具

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。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is AWS Amplify Gen 2 Documentation MCP Server?

AWS Amplify Gen 2 Documentation MCP Server is an unofficial Model Context Protocol (MCP) server that provides tools to fetch and search AWS Amplify Gen 2 documentation pages. It is designed for developers who want to query official Amplify Gen 2 docs through an AI assistant such as Amazon Q or Claude.

How to use AWS Amplify Gen 2 Documentation MCP Server?

Install uv and Python 3.13+, then add the configuration block shown in the README to your MCP config file (e.g., .amazonq/mcp.json for Amazon Q). Once configured, you can ask natural‑language questions such as "How can I create custom resources in Amplify Gen 2?" and the server will fetch or search the documentation to answer.

Key features of AWS Amplify Gen 2 Documentation MCP Server

  • Fetch an Amplify Gen 2 documentation page and convert it to markdown
  • Search Amplify Gen 2 documentation using the official search API (Algolia)
  • Integrates with MCP‑compatible assistants (Amazon Q, Claude)
  • Lightweight, no persistent database – queries are made on demand
  • Provides two tools: read_amplify_documentation and search_amplify_documentation

Use cases of AWS Amplify Gen 2 Documentation MCP Server

  • Retrieve a specific documentation page as formatted markdown for offline reading
  • Search for topics across the entire Amplify Gen 2 documentation set
  • Get code examples, permission details, or feature explanations during development
  • Power an AI assistant that answers questions about Amplify Gen 2 without leaving the IDE or chat

常见问题

1

Is this an official AWS product?

No, this is an unofficial MCP server. It is inspired by and references the official AWS Documentation MCP Server (awslabs/mcp).

2

What dependencies are required?

You need `uv` (from Astral) and Python 3.13 or newer. The server runs via `uvx`.

3

What tools does the server expose?

It exposes two tools: `read_amplify_documentation` (fetches a page and converts it to markdown) and `search_amplify_documentation` (searches documentation via Algolia).

4

How do I configure the server for Amazon Q?

Create (if it does not exist) a file named `.amazonq/mcp.json` in the directory where `q chat` runs and add the JSON configuration shown in the README.

5

Does the server store any data locally?

No, all data is fetched on demand from the AWS Amplify Gen 2 documentation site and search API. No persistent storage is used.

评论

记忆与知识 分类下的更多 MCP 服务器

Orcha

westonhancock

Orcha is a unified context layer for AI tools and agents. It stores and indexes and exposes organizational, team, or individual knowledge. Files, structured databases, and connected sources live in one workspace, and age

Codebase Memory

DeusData

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 162 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

46.7K

LoreKeeper RPG (lorekeeper.com)

LoreKeeper Ltd

Mess in, magic out: pour in your D&D and TTRPG notes and LoreKeeper keeps them as a private store for your world. Ask Claude or ChatGPT about it, or build a sourcebook.

ctxfile

ctxfile

Local-first MCP server that snapshots your project's working state into one context object. Open-core, privacy-first.

2

agentleFS

agentleFS

One permissioned folder your team and your AI agents both log into.

广告合作