Click on "Install 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., "@Markdown-To-Notion convert this markdown to notion format: # Heading\n\nSome content with bold text"
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.
一个将Markdown内容转换为Notion API兼容格式的MCP服务器，适用于内容管理和开发集成。 An MCP server that converts Markdown content to Notion API-compatible formats, suitable for content management and development integration.## 工具列表 Tool List
本MCP服务封装下列工具，可让模型通过标准化接口调用以下功能。 本MCP服务封装下列工具，可让模型通过标准化接口调用以下功能。
工具 Tool | 描述 Description |
markdown-to-notion | Convert markdown content to notion json page content |
工具在线测试： https://mcp.xiaobenyang.com/inspector/1777316659401731
Online Tool test https://mcp.xiaobenyang.com/inspector/1777316659401731
Related MCP server: MCP Notion Server (@suncreation)
如何获取 XBY-APIKEY ？ How to get XBY-APIKEY ?
访问小笨羊科技网站 https://xiaobenyang.com，注册用户即可获得APIKEY Visit XiaoBenYang website https://xiaobenyang.com, register and get the APIKEY.
{
"mcpServers": {
"Markdown转Notion转换器": {
"headers": {
"XBY-APIKEY": "<YOUR_XBY_APIKEY>"
},
"type": "sse",
"url": "https://mcp.xiaobenyang.com/1777316659401731/sse"
}
}
}{
"mcpServers": {
"Markdown转Notion转换器": {
"headers": {
"XBY-APIKEY": "<YOUR_XBY_APIKEY>"
},
"type": "streamable_http",
"url": "https://mcp.xiaobenyang.com/1777316659401731/mcp"
}
}
}{
"mcpServers": {
"Markdown转Notion转换器": {
"command": "npx",
"args": [
"-y",
"xiaobenyang-mcp"
],
"env": {
"XBY_APIKEY": "<YOUR_XBY_APIKEY>",
"mcpId": "1777316659401731",
},
"transport": "stdio"
}
}
}
Convert markdown content to notion json page content
| Name | Required | Description | Default |
|---|---|---|---|
| markdown | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the conversion function without mentioning any behavioral traits: no information about error handling, performance characteristics, rate limits, authentication needs, or what happens to invalid markdown. This leaves the agent with significant uncertainty about how the tool behaves in practice.
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 extremely concise - a single sentence that directly states the tool's function with zero wasted words. It's perfectly front-loaded with the essential information. This is an excellent example of efficiency in description writing.
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?
Given the tool's purpose (format conversion), absence of annotations, no output schema, and 0% schema coverage, the description is insufficiently complete. It doesn't address what the output looks like (beyond 'notion json page content'), error conditions, or practical usage considerations. For a conversion tool with no structured documentation support, more context is needed.
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 description coverage is 0% (no parameter descriptions in schema), and the tool has 1 parameter. The description mentions 'markdown content' but provides no additional semantic context about the parameter: no format requirements, size limits, supported markdown features, or examples. It doesn't compensate for the complete lack of schema documentation.
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 purpose: 'Convert markdown content to notion json page content' - a specific verb ('convert') and resources ('markdown content' to 'notion json page content'). It's unambiguous about what transformation it performs. However, with no sibling tools mentioned, there's no explicit differentiation from alternatives, preventing a perfect score.
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. It doesn't mention prerequisites, constraints, or typical use cases. While the purpose is clear, there's complete absence of contextual usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
With only one tool, there is no possibility of confusion or overlap between tools, as there are no other tools to compare it against. The tool's purpose is singular and clearly defined, eliminating any ambiguity in tool selection.
Since there is only one tool, it inherently maintains perfect consistency with itself. The tool name follows a clear verb-object pattern (markdown-to-notion), which is straightforward and descriptive for its function.
A single tool is generally too few for a server's scope, as it limits functionality and suggests an incomplete or overly narrow implementation. While the tool's purpose is clear, one tool often indicates a minimal surface that may not cover related operations or workflows effectively.
The server's domain appears to involve converting markdown to Notion content, but with only a conversion tool, there are significant gaps. Missing operations might include retrieving markdown, updating Notion pages, handling errors, or managing conversions in bulk, which could lead to agent failures in broader tasks.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Markdown-based note-taking with a hosted MCP server. Your notes serve you and your AI.
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Document-to-Markdown MCP server — convert PDF, Office and HTML into LLM-ready Markdown.
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