MCP Markdown Conversion Server
MCP-Server zu Markdown
Englisch |简体中文
Ein leistungsstarker Model Context Protocol (MCP)-Server, der Cloudflare-KI-Dienste nutzt, um verschiedene Dateiformate in Markdown-Beschreibungen zu konvertieren. Dieser Server bietet eine standardisierte Schnittstelle für die nahtlose Dateikonvertierung und Beschreibungsgenerierung.
Hauptmerkmale
Nahtlose Integration mit Cloudflare-KI-Diensten
Effiziente Generierung von Markdown-Beschreibungen
Umfassende Dateiformatunterstützung
Native Cloudflare tomarkdown API-Integration
Benutzerfreundliche MCP-Schnittstelle
Plattformübergreifende Kompatibilität
Related MCP server: Textin MCP Server
Unterstützte Dateiformate
Kategorie | Dateierweiterungen |
Unterlagen | |
Bilder | .jpeg, .jpg, .png, .webp, .svg |
Webinhalte | .html |
Daten | .xml, .csv |
Tabellenkalkulationen | .xlsx, .xlsm, .xlsb, .xls, .et, .ods, .numbers |
Systemanforderungen
Node.js 18 oder höher
Gültiges Cloudflare API-Token
Aktive Cloudflare-Konto-ID
Installation
Installation über Smithery
So installieren Sie Markdown转换服务器 für Claude Desktop automatisch über Smithery :
npx -y @smithery/cli install @FradSer/mcp-server-to-markdown --client claudeManuelle Installation
Globale Installation mit npm:
npm install -g mcp-server-to-markdownMCP-Client-Konfiguration
Cursor-Integration
Navigieren Sie zu den Cursoreinstellungen
Wählen Sie „MCP“ aus der Seitenleiste
Wählen Sie „Neuen globalen MCP-Server hinzufügen“
Wenden Sie die folgende Konfiguration an:
{ "mcpServers": { "to-markdown": { "command": "mcp-server-to-markdown", "args": [ "CLOUDFLARE_API_TOKEN": "your_api_token" "CLOUDFLARE_ACCOUNT_ID": "your_account_id" ] } } }
Claude Desktop-Setup
Fügen Sie Ihrer claude_desktop_config.json Folgendes hinzu:
{
"mcpServers": {
"to-markdown": {
"command": "mcp-server-to-markdown",
"args": [
"CLOUDFLARE_API_TOKEN": "your_api_token"
"CLOUDFLARE_ACCOUNT_ID": "your_account_id"
]
}
}
}ChatWise-Konfiguration
Starten Sie ChatWise
Zugriffseinstellungen
Wählen Sie den Abschnitt „Tools“
Klicken Sie auf „+“, um ein neues Werkzeug hinzuzufügen
Konfigurieren Sie mit diesen Parametern:
Typ:
stdioID:
to-markdownBefehl:
mcp-server-to-markdownArgumente:
CLOUDFLARE_API_TOKEN=your_api_token CLOUDFLARE_ACCOUNT_ID=your_account_id
API-Referenz
To-Markdown-Tool
Konvertiert verschiedene Dateiformate in Markdown-Beschreibungen.
Eingabeparameter:
filePaths: Array (erforderlich) – Liste der zu verarbeitenden Dateipfade
Antwortstruktur:
[
{
"filename": "example.pdf",
"mimeType": "application/pdf",
"description": "Generated Markdown description",
"tokens": 123
}
]Entwicklungshandbuch
Erste Schritte
Umgebung klonen und einrichten:
git clone <repository-url>
cd mcp-server-to-markdown
cp .env.example .envKonfigurieren Sie die Cloudflare-Anmeldeinformationen:
CLOUDFLARE_API_TOKEN=your_api_token
CLOUDFLARE_ACCOUNT_ID=your_account_idInstallieren Sie Abhängigkeiten und erstellen Sie:
npm install
npm run buildProjektstruktur
.
├── src/ # Source code
├── dist/ # Compiled output
├── types.ts # Type definitions
└── .env # Environment configurationVerfügbare Skripte
npm run build– TypeScript-Code erstellennpm run inspect– Mit MCP-Inspector ausführen
Anwendungsbeispiel
const result = await toMarkdown({
filePaths: [
"/path/to/document.pdf",
"/path/to/image.jpg"
]
});Lizenz
MIT-Lizenz
Dieses Projekt wird von Frad LEE betreut
Available Tools
1 toolto-markdownC
Generate markdown description for files including PDF (.pdf), Images (.jpeg, .jpg, .png, .webp, .svg), HTML (.html), XML (.xml), Microsoft Office (.xlsx, .xlsm, .xlsb, .xls, .et), Open Document Format (.ods), CSV (.csv), and Apple Documents (.numbers)
| Name | Required | Description | Default |
|---|---|---|---|
| filePaths | Yes | Array of absolute file paths to generate descriptions for |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions what the tool does but lacks behavioral details like whether it processes files locally or remotely, error handling for unsupported formats, performance characteristics, or output format specifics. The description is functional but minimal.
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, efficient sentence that front-loads the core purpose and lists supported file types without unnecessary elaboration. Every word contributes to understanding the tool's scope, making it appropriately concise.
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 no annotations and no output schema, the description is incomplete. It doesn't explain what the generated markdown includes, how errors are handled, or any behavioral traits. For a tool with one parameter but significant implicit complexity (file processing), 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 100%, so the schema already documents the 'filePaths' parameter. The description adds no additional parameter semantics beyond implying file type support, which is partially covered by the schema's lack of constraints. Baseline 3 is appropriate as the schema does the heavy lifting.
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: 'Generate markdown description for files' and lists specific file types it supports. It uses a specific verb ('Generate') and identifies the resource ('files'), but since there are no sibling tools, it doesn't need to differentiate from alternatives.
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 or any contextual prerequisites. It simply lists supported file types without indicating scenarios where this tool is appropriate or any limitations.
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.
1 tool update
v1.0.0- First observed
to-markdown
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'to-markdown' has a clearly defined and distinct purpose: converting various file formats to markdown descriptions.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'to-markdown' follows a clear verb-object pattern that is appropriate for its function.
A single tool is too few for a server with a broad scope like 'Markdown Conversion Server' that handles multiple file types. This thin surface may force agents to rely on this one tool for all conversion tasks, lacking specialized operations for different formats or scenarios.
The tool set is severely incomplete for the server's purpose. While 'to-markdown' covers conversion, there are obvious gaps such as no tools for validating markdown, handling conversion errors, or providing metadata about supported formats, which limits agent workflows.
Maintenance
Related MCP Connectors
Document-to-Markdown MCP server — convert PDF, Office and HTML into LLM-ready Markdown.
Document conversion MCP server: PDF to Markdown, image OCR, spreadsheet parsing.
Document to Markdown MCP server: PDF, Word, PowerPoint, Excel and HTML, with OCR for large files.
Convert PDF, Word, Excel and scanned documents to Markdown, tables and RAG chunks. OCR.
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