md2card-mcp-server
Provides tools for scraping WeChat public account articles and converting them to Markdown format, including extracting title, author, description, and cover image.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@md2card-mcp-serverConvert this markdown to a knowledge card: # Hello World"
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.
MD2Card MCP 服务器
homepage: https://md2card.cn
MD2Card Markdown 转知识卡片 将 Markdown 文档转换为精美的知识卡片,支持多种风格
安装与使用
方法一:使用 npx(推荐)
直接使用 npx 运行(需要设置 API 密钥环境变量):
# 设置API密钥并运行
MD2CARD_API_KEY="您的API密钥" npx md2card-mcp-server方法二:全局安装
# 安装
npm install -g md2card-mcp-server
# 运行(需要设置API密钥环境变量)
MD2CARD_API_KEY="您的API密钥" md2card-mcp-server方法三:本地配置
clone 项目到本地,找到 index.js 路径替换到客户端 mcp 配置文件中
Related MCP server: Little Red Book Card MCP
功能特性
支持 22 种主题样式:苹果备忘录 波普艺术 艺术装饰 玻璃拟态 温暖柔和 简约高级灰 梦幻渐变 清新自然 紫色小红书 笔记本 暗黑科技 复古打字机 水彩艺术 中国传统 儿童童话 商务简报 日本杂志 极简黑白 赛博朋克
智能尺寸适配
三种内容拆分模式:默认自动拆分
通过 MCP 协议提供标准化接口
新功能:支持直接读取 Markdown 文件
新功能:支持通过 type 参数直接指定卡片类型/尺寸
新功能:支持抓取微信公众号文章并转换为 Markdown 格式
新功能:自动提取文章标题、作者、描述和封面图片
使用方法
方法一:提供 Markdown 内容
{
"markdown": "# 标题\n\n内容"
}方法二:提供 Markdown 文件路径
{
"markdownFile": "/path/to/your/file.md"
}方法三:指定卡片类型/尺寸
可以通过type参数直接指定卡片类型,支持以下类型:
小红书:440x586
正方形:500x500
手机海报:440x782
A4 纸打印:595x842
{
"markdown": "# 标题\n\n内容",
"type": "小红书"
}也可以通过 width 和 height 参数指定:
{
"markdown": "# 标题\n\n内容",
"width": "小红书",
"height": 586
}方法四:抓取微信公众号文章
使用 wechat_scraper 工具抓取微信公众号文章:
{
"url": "https://mp.weixin.qq.com/s/your-article-id"
}返回结果包含完整的 Markdown 格式文章,包括:
文章标题
作者信息
文章描述
封面图片
正文内容
客户端配置
通用 MCP 客户端配置
在 MCP 客户端配置文件中添加以下内容:
{
"md2card-server": {
"command": "npx",
"args": ["md2card-mcp-server@latest"],
"env": {
"MD2CARD_API_KEY": "您的API密钥"
}
}
}Cursor 客户端配置
在 Cursor 的 MCP 客户端配置文件中添加以下内容:
{
"md2card-server": {
"command": "npx",
"args": ["-y", "md2card-mcp-server@latest"],
"env": {
"MD2CARD_API_KEY": "您的API密钥"
}
}
}注意:MD2CARD_API_KEY 环境变量是必需的,只有在实际运行时才会检查此环境变量。安装包时不需要此环境变量。
Available Tools
2 toolsmd2card_apiC
将 Markdown 文档转换为精美的知识卡片
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | 卡片类型(小红书/正方形/手机海报/A4纸打印) | |
| theme | No | 卡片主题(默认:苹果备忘录)(苹果备忘录/线圈笔记本/波普艺术/字节范/阿里橙/艺术装饰/玻璃拟态/温暖柔和/简约高级灰/梦幻渐变/清新自然/紫色小红书/笔记本/暗黑科技/复古打字机/水彩艺术/中国传统/儿童童话/商务简报/日本杂志/极简黑白/赛博朋克/青野晨光) | apple-notes |
| width | No | 卡片宽度 | |
| height | No | 卡片高度 | |
| mdxMode | No | 是否启用MDX模式 | |
| markdown | No | Markdown内容 | |
| splitMode | No | 卡片拆分模式 | noSplit |
| themeMode | No | 卡片主题模式(默认模式/粉蓝模式/薄荷模式/紫色模式/蓝色模式/粉色模式/黄色模式/亮色模式/暗黑模式) | |
| markdownFile | No | Markdown文件路径 | |
| overHiddenMode | No | 是否启用超出高度隐藏 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must disclose behavioral traits. It only provides a high-level description without mentioning any side effects, output format, or operational details such as file handling or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the core function without unnecessary words, earning maximum conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 10 parameters, no output schema, and no annotations. A one-sentence description does not adequately cover usage context, expected output, or edge cases, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no parameter-specific information beyond what the schema already documents, so no additional value is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb (convert) and resource (Markdown documents to knowledge cards). It lacks explicit differentiation from sibling tools, but the sibling is unrelated, so the purpose is nonetheless clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It doesn't mention any scenarios or exclusions, leaving the agent to infer usage from the name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wechat_scraperB
抓取微信公众号文章并转换为 Markdown 格式
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | 微信公众号文章的 URL 地址 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. It only states the core fetch-and-convert action without details on error handling, network requirements, anti-scraping issues, or the exact output format. This is a significant gap for a scraper tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence that is front-loaded and contains no redundant information. Every word contributes meaning, making it an efficient and well-structured statement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a scraper with one parameter and no output schema, yet the description does not explicitly explain what the return value is (e.g., whether Markdown is returned as a string, file, or in another format). It also lacks information about error behavior or limitations, leaving the agent under-informed for a non-trivial operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the single 'url' parameter with a clear description, achieving 100% schema coverage. The tool description adds no additional context beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: fetching WeChat official account articles and converting them to Markdown. The verb '抓取' specifies the action and resource explicitly, and it distinguishes itself from the sibling tool md2card_api, which likely performs the reverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or edge cases. While the sibling tool exists, no differentiation is offered, leaving the agent without context for selecting this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
v0.1.10- First observed
md2card_api - First observed
wechat_scraper
TDQS
Scored across 2 tools
The two tools have clear, non-overlapping purposes: md2card_api converts Markdown to knowledge cards, while wechat_scraper fetches WeChat articles and converts them to Markdown. An agent can easily distinguish when to use each.
The naming pattern is inconsistent: 'md2card_api' uses an acronym-plus-suffix style, while 'wechat_scraper' uses a plain noun phrase. Neither follows a verb_noun convention, and the two names have no shared structural pattern.
With only two tools, the server feels minimal. However, the niche scope (Markdown-to-card conversion with a WeChat import pathway) arguably justifies a small surface, but it is still on the borderline of being too thin.
The core workflow is covered: scrape WeChat content to Markdown, then convert Markdown to cards. Minor gaps exist (e.g., no direct URL-to-card conversion or card customization options), but the primary pipeline is functional.
Maintenance
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