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Wexin Read MCP

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Bwkyd

能够让大模型阅读微信公众号文章,使用浏览器模拟绕过反爬虫。

PublisherBwkyd
Repositorywexin-read-mcp
LanguagePython
Forks
58
Stars
451
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Wexin Read MCP exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    451 stars and 58 forks from the linked repository.

Weixin MCP - 微信文章阅读器

一个极简的MCP,让大模型能够阅读微信公众号文章。

核心功能

  • 🎭 浏览器模拟:使用 Playwright 完整模拟浏览器环境
  • 📝 内容提取:自动提取标题、作者、发布时间、正文内容
  • ⚡ 简洁实现:最少的代码实现核心功能

工作流程

  1. 用户发送URL和需求给大模型
  2. 大模型调用MCP工具
  3. MCP获取文章内容发送给大模型
  4. 大模型根据文章内容输出自然语言

技术栈

  • Python 3.10+
  • fastmcp - MCP框架
  • url-md (Rust 单二进制) - 反爬 + Markdown 抽取一步到位
  • pyyaml - frontmatter 解析

v0.3.0 升级说明:抓取层从 agent-browser 4 次子进程 + BeautifulSoup 解析,简化为 单次调用 url-md md <url>。url-md 内部已处理反爬 / 微信正文抽取 / Markdown 转换 / frontmatter 生成。依赖减少,content 字段升级为 Markdown(保留图片引用 / 列表 / 标题层级)。MCP 协议接口零变化,现有 Claude/Cursor 配置无需调整。

v0.2.0 升级说明: 原 Playwright 方案被微信加强反爬打穿 (issue #3)。抓取层改为委托给 agent-browser(Apache-2.0 开源 Rust 项目)。v0.3.0 起已迁移到 url-md。

快速开始

1. 安装 url-md (v0.3.0 起必需)

bash
# macOS / Linux
curl -fsSL https://raw.githubusercontent.com/Bwkyd/url-md/main/install.sh | bash

# Windows (PowerShell)
irm https://raw.githubusercontent.com/Bwkyd/url-md/main/install.ps1 | iex

# 验证
url-md --version

6 秒从零到可用。7 MB 单二进制,无需 Chrome 等外部依赖(微信永久链走 reqwest 快路)。

2. 安装 Python 依赖

bash
pip install -r requirements.txt

3. 配置

json
{
  "mcpServers": {
    "weixin-reader": {
      "command": "python",
      "args": [
        "C:/Users/你的用户名/Desktop/wx-mcp/wx-mcp-server/src/server.py"
      ]
    }
  }
}

注意: 请将路径替换为你的实际项目路径。

使用示例

在Claude中直接使用:

请帮我总结这篇文章:https://mp.weixin.qq.com/s/nEJhdxGea-KLZA_IGw9R5A

Claude会自动调用read_weixin_article工具获取文章内容并进行分析。 alt text

功能说明

read_weixin_article(url: str)

读取微信公众号文章内容。

参数:

  • url: 微信文章URL,格式: https://mp.weixin.qq.com/s/xxx

返回:

json
{
  "success": true,
  "title": "文章标题",
  "author": "作者名",
  "publish_time": "2025-11-05",
  "content": "# 文章正文\n\n![封面](https://...)\n\n段落内容...",
  "cover_url": "https://mmbiz.qpic.cn/.../wx_fmt=jpeg",
  "error": null
}

v0.3.0 起 content 字段是 Markdown 格式(v0.2.0 及以前是纯文本)。如果下游 agent/prompt 已按纯文本处理,可在返回前自行去除 Markdown 语法,或保留 Markdown 让 LLM 原生理解更好。

注意事项

  • ⚠️ 仅用于个人学习和研究
  • ⚠️ 遵守微信公众平台服务协议
  • ⚠️ 不建议高频爬取(建议间隔 > 2秒)
  • ⚠️ 不用于商业用途

Installation

TypingMind
{
  "mcpServers": {
    "wexin-read-mcp": {
      "command": "python",
      "args": [
        "C:/Users/你的用户名/Desktop/wx-mcp/wx-mcp-server/src/server.py"
      ]
    }
  }
}

Use Wexin Read MCP MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Wexin Read MCP is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Wexin Read MCP as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Wexin Read MCP MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "wexin-read-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Wexin Read MCP MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Wexin Read MCP MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Wexin Read MCP to help me with this task?
Wexin Read MCP
Sure. I read it.
Here is what I found using Wexin Read MCP.

Frequently asked questions

What is the Wexin Read MCP MCP server used for?

Wexin Read MCP is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Wexin Read MCP MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Wexin Read MCP with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Wexin Read MCP MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Wexin Read MCP connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Wexin Read MCP MCP to TypingMind?

Wexin Read MCP runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Wexin Read MCP MCP provide in TypingMind?

Wexin Read MCP exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Wexin Read MCP MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Wexin Read MCP requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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