Which integrations are available for this server?

Allows converting WeChat Official Account articles into clean Markdown files with locally downloaded images.

How do I use wechat-to-md?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@wechat-to-md convert https://mp.weixin.qq.com/s/example-article to markdown" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

wechat-to-md

by bzd6661

Overview Schema Related Servers Score Discussions

Python

Local

wechat-article-for-ai

English | 中文

English

A modular Python tool that converts WeChat Official Account (微信公众号) articles into clean Markdown files with locally downloaded images. Designed for both human use (CLI) and AI agent integration (MCP server + SKILL.md).

Features

Anti-detection scraping — Uses Camoufox (stealth Firefox) to bypass WeChat's bot detection
Smart page loading — networkidle wait instead of hardcoded sleep
Retry logic — 3× exponential backoff for page fetching, 3× linear backoff for image downloads
CAPTCHA detection — Explicit detection with actionable error messages
Batch processing — Multiple URLs via args or file input
Image localization — Concurrent async downloads with Content-Type based extension inference
Code block preservation — Language detection, CSS counter garbage filtering
Media extraction — Handles WeChat's <mpvoice> audio and <mpvideo> video elements
YAML frontmatter — Structured metadata (title, author, date, source)
MCP server — Expose as tools for any MCP-compatible AI client
SKILL.md — Ready for Claude Code skill integration

Installation

git clone https://github.com/bzd6661/wechat-article-for-ai.git
cd wechat-article-for-ai
pip install -r requirements.txt

Camoufox browser will be auto-downloaded on first run.

Usage

CLI — Single Article

python main.py "https://mp.weixin.qq.com/s/ARTICLE_ID"

CLI — Batch from File

python main.py -f urls.txt -o ./output -v

CLI Options

Flag	Description
`urls`	One or more WeChat article URLs
`-f, --file FILE`	Text file with URLs (one per line, `#` for comments)
`-o, --output DIR`	Output directory (default: `./output`)
`-c, --concurrency N`	Max concurrent image downloads (default: 5)
`--no-images`	Skip image download, keep remote URLs
`--no-headless`	Show browser window (for solving CAPTCHAs)
`--force`	Overwrite existing output
`--no-frontmatter`	Use blockquote metadata instead of YAML frontmatter
`-v, --verbose`	Enable debug logging

MCP Server

Run as an MCP server for AI tool integration:

python mcp_server.py

Tools exposed:

convert_article — Convert a single WeChat article to Markdown
batch_convert — Convert multiple articles in one call

MCP client configuration (e.g. claude_desktop_config.json):

{
  "mcpServers": {
    "wechat-to-md": {
      "command": "python",
      "args": ["mcp_server.py"],
      "cwd": "/path/to/wechat-article-for-ai"
    }
  }
}

Output Structure

output/
  <article-title>/
    <article-title>.md
    images/
      img_001.png
      img_002.jpg
      ...

Project Structure

wechat_to_md/
  __init__.py        # Package init, public API
  errors.py          # CaptchaError, NetworkError, ParseError
  utils.py           # Logging, filename sanitizer, timestamp, image ext inference
  scraper.py         # Camoufox + networkidle + retry with exponential backoff
  parser.py          # BeautifulSoup: metadata, code blocks, media, noise removal
  converter.py       # markdownify + YAML frontmatter + image URL replacement
  downloader.py      # httpx async + retry per image + Content-Type inference
  cli.py             # argparse CLI with batch support
  mcp_server.py      # FastMCP server with convert_article / batch_convert
main.py              # CLI entry point
mcp_server.py        # MCP server entry point
SKILL.md             # AI skill definition

Troubleshooting

Problem	Solution
CAPTCHA / verification page	Run with `--no-headless` to solve manually
Empty content	WeChat may be rate-limiting; wait and retry
Image download failures	Failed images keep remote URLs; re-run with `--force`

License

MIT

Related MCP server: WeChat Article Extractor

中文

一个模块化的 Python 工具，将微信公众号文章转换为干净的 Markdown 文件并下载图片到本地。同时支持人工使用（CLI）和 AI 智能体集成（MCP 服务器 + SKILL.md）。

功能特点

反检测抓取 — 使用 Camoufox（隐身 Firefox）绕过微信的反爬机制
智能页面等待 — 使用 networkidle 替代硬编码的 sleep
重试机制 — 页面加载 3 次指数退避重试，图片下载 3 次线性退避重试
验证码检测 — 明确识别验证码页面并给出可操作的错误提示
批量处理 — 支持多个 URL 参数或从文件读取
图片本地化 — 异步并发下载，基于 Content-Type 推断图片格式
代码块保留 — 自动检测编程语言，过滤 CSS 计数器垃圾文本
媒体提取 — 处理微信的 <mpvoice> 音频和 <mpvideo> 视频元素
YAML 元数据 — 结构化的 frontmatter（标题、作者、日期、来源）
MCP 服务器 — 暴露为工具，供任何 MCP 兼容的 AI 客户端调用
SKILL.md — 可直接作为 Claude Code 技能使用

安装

git clone https://github.com/bzd6661/wechat-article-for-ai.git
cd wechat-article-for-ai
pip install -r requirements.txt

Camoufox 浏览器会在首次运行时自动下载。

使用方法

CLI — 单篇文章

python main.py "https://mp.weixin.qq.com/s/文章ID"

CLI — 批量转换

python main.py -f urls.txt -o ./output -v

CLI 参数

参数	说明
`urls`	一个或多个微信文章链接
`-f, --file 文件`	包含 URL 的文本文件（每行一个，`#` 为注释）
`-o, --output 目录`	输出目录（默认：`./output`）
`-c, --concurrency N`	图片下载最大并发数（默认：5）
`--no-images`	跳过图片下载，保留远程链接
`--no-headless`	显示浏览器窗口（用于手动解决验证码）
`--force`	覆盖已有的输出目录
`--no-frontmatter`	使用引用块格式的元数据，而非 YAML frontmatter
`-v, --verbose`	启用调试日志

MCP 服务器

作为 MCP 服务器运行，供 AI 工具集成：

python mcp_server.py

暴露的工具：

convert_article — 转换单篇微信文章为 Markdown
batch_convert — 批量转换多篇文章

MCP 客户端配置（如 claude_desktop_config.json）：

{
  "mcpServers": {
    "wechat-to-md": {
      "command": "python",
      "args": ["mcp_server.py"],
      "cwd": "/path/to/wechat-article-for-ai"
    }
  }
}

输出结构

output/
  <文章标题>/
    <文章标题>.md
    images/
      img_001.png
      img_002.jpg
      ...

项目结构

wechat_to_md/
  __init__.py        # 包初始化，公共 API
  errors.py          # CaptchaError, NetworkError, ParseError
  utils.py           # 日志、文件名清理、时间戳、图片格式推断
  scraper.py         # Camoufox + networkidle + 指数退避重试
  parser.py          # BeautifulSoup：元数据、代码块、媒体、噪音移除
  converter.py       # markdownify + YAML frontmatter + 图片 URL 替换
  downloader.py      # httpx 异步 + 逐图重试 + Content-Type 推断
  cli.py             # argparse CLI，支持批量处理
  mcp_server.py      # FastMCP 服务器
main.py              # CLI 入口
mcp_server.py        # MCP 服务器入口
SKILL.md             # AI 技能定义文件

常见问题

问题	解决方法
出现验证码 / 环境异常	使用 `--no-headless` 手动解决验证码
内容为空	微信可能在限流，等几分钟再试
图片下载失败	失败的图片会保留远程链接，用 `--force` 重新运行

许可证

MIT

This server cannot be installed

license - not found

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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