About MCP Server To Markdown
MCP Server To Markdown is an MCP server that uses Cloudflare AI services to convert files such as PDFs, images, HTML, XML, CSV and spreadsheets into Markdown descriptions. It offers a standardized interface for batch file conversion.
Key features
- 01Generates Markdown descriptions using Cloudflare AI services
- 02Supports PDF, image, web, data and spreadsheet formats
- 03to-markdown tool accepts a list of file paths
- 04Returns filename, MIME type, description and token count
Use cases
- 01Converting PDF documents into Markdown descriptions for an LLM
- 02Generating text descriptions for images or SVG files
- 03Batch processing Excel and CSV files
MCP support
This project is an MCP server that exposes file conversion through the to-markdown tool to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP Server To Markdown 
English | 简体中文
A powerful Model Context Protocol (MCP) server that leverages Cloudflare AI services to convert various file formats into Markdown descriptions. This server provides a standardized interface for seamless file conversion and description generation.
Key Features
- Seamless integration with Cloudflare AI services
- Efficient Markdown description generation
- Comprehensive file format support
- Native Cloudflare tomarkdown API integration
- User-friendly MCP interface
- Cross-platform compatibility
Supported File Formats
| Category | File Extensions |
|---|---|
| Documents | |
| Images | .jpeg, .jpg, .png, .webp, .svg |
| Web Content | .html |
| Data | .xml, .csv |
| Spreadsheets | .xlsx, .xlsm, .xlsb, .xls, .et, .ods, .numbers |
System Requirements
- Node.js 18 or later
- Valid Cloudflare API Token
- Active Cloudflare Account ID
Installation
Installing via Smithery
To install Markdown转换服务器 for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @FradSer/mcp-server-to-markdown --client claude
Manual Installation
Install globally using npm:
npm install -g mcp-server-to-markdown
MCP Client Configuration
Cursor Integration
- Navigate to Cursor settings
- Select "MCP" from the sidebar
- Choose "Add new global MCP server"
- Apply the following configuration:
{ "mcpServers": { "to-markdown": { "command": "mcp-server-to-markdown", "args": [ "CLOUDFLARE_API_TOKEN": "your_api_token" "CLOUDFLARE_ACCOUNT_ID": "your_account_id" ] } } }
Claude Desktop Setup
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"to-markdown": {
"command": "mcp-server-to-markdown",
"args": [
"CLOUDFLARE_API_TOKEN": "your_api_token"
"CLOUDFLARE_ACCOUNT_ID": "your_account_id"
]
}
}
}
ChatWise Configuration
- Launch ChatWise
- Access Settings
- Select Tools section
- Click "+" to add new tool
- Configure with these parameters:
- Type:
stdio - ID:
to-markdown - Command:
mcp-server-to-markdown - Args:
CLOUDFLARE_API_TOKEN=your_api_token CLOUDFLARE_ACCOUNT_ID=your_account_id
- Type:
API Reference
to-markdown Tool
Converts various file formats to Markdown descriptions.
Input Parameters:
filePaths: Array (required) - List of file paths to process
Response Structure:
[
{
"filename": "example.pdf",
"mimeType": "application/pdf",
"description": "Generated Markdown description",
"tokens": 123
}
]
Development Guide
Getting Started
- Clone and setup environment:
git clone <repository-url>
cd mcp-server-to-markdown
cp .env.example .env
- Configure Cloudflare credentials:
CLOUDFLARE_API_TOKEN=your_api_token
CLOUDFLARE_ACCOUNT_ID=your_account_id
- Install dependencies and build:
npm install
npm run build
Project Structure
.
├── src/ # Source code
├── dist/ # Compiled output
├── types.ts # Type definitions
└── .env # Environment configuration
Available Scripts
npm run build- Build TypeScript codenpm run inspect- Run with MCP inspector
Usage Example
const result = await toMarkdown({
filePaths: [
"/path/to/document.pdf",
"/path/to/image.jpg"
]
});
License
MIT License
This project is maintained by Frad LEE
Comments
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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.