Dumpling AI's MCP server provides a robust implementation of the Model Context Protocol that connects with Dumpling AI's suite of tools. This server gives you access to data scraping, content processing, knowledge management, AI agents, and code execution capabilities through an extensive collection of APIs.
The easiest way to install the MCP server for Claude Desktop is via Smithery:
npx -y @smithery/cli install @Dumpling-AI/mcp-server-dumplingai --client claude
You can install the package globally:
npm install -g mcp-server-dumplingai
To run the server, use your Dumpling API key:
env DUMPLING_API_KEY=your_api_key npx -y mcp-server-dumplingai
To use the server with Cursor (version 0.45.6+):
{
"mcpServers": {
"dumplingai": {
"command": "npx",
"args": ["-y", "mcp-server-dumplingai"],
"env": {
"DUMPLING_API_KEY": "<your-api-key>"
}
}
}
}
For Windows users experiencing issues, try:
cmd /c "set DUMPLING_API_KEY=your-api-key && npx -y mcp-server-dumplingai"
The server requires one environment variable:
DUMPLING_API_KEY
: Your Dumpling AI API keyThe server provides several tools for accessing and processing data from various sources.
Extract transcripts from YouTube videos:
{
"name": "get-youtube-transcript",
"arguments": {
"videoUrl": "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
"includeTimestamps": true,
"timestampsToCombine": 3,
"preferredLanguage": "en"
}
}
Perform Google web searches with optional content scraping:
{
"name": "search",
"arguments": {
"query": "machine learning basics",
"country": "us",
"language": "en",
"dateRange": "pastMonth",
"scrapeResults": true,
"numResultsToScrape": 3,
"scrapeOptions": {
"format": "markdown",
"cleaned": true
}
}
}
Get Google search autocomplete suggestions:
{
"name": "get-autocomplete",
"arguments": {
"query": "how to learn",
"country": "us",
"language": "en",
"location": "New York"
}
}
Search for locations on Google Maps:
{
"name": "search-maps",
"arguments": {
"query": "coffee shops",
"gpsPositionZoom": "37.7749,-122.4194,14z",
"language": "en",
"page": 1
}
}
Search for detailed place information:
{
"name": "search-places",
"arguments": {
"query": "hotels in paris",
"country": "fr",
"language": "en",
"page": 1
}
}
Search for news articles:
{
"name": "search-news",
"arguments": {
"query": "climate change",
"country": "us",
"language": "en",
"dateRange": "pastWeek"
}
}
Retrieve reviews for businesses or places:
{
"name": "get-google-reviews",
"arguments": {
"businessName": "Eiffel Tower",
"location": "Paris, France",
"limit": 10,
"sortBy": "relevance"
}
}
Extract content from web pages:
{
"name": "scrape",
"arguments": {
"url": "https://example.com",
"format": "markdown",
"cleaned": true,
"renderJs": true
}
}
Recursively crawl websites:
{
"name": "crawl",
"arguments": {
"baseUrl": "https://example.com",
"maxPages": 10,
"crawlBeyondBaseUrl": false,
"depth": 2,
"scrapeOptions": {
"format": "markdown",
"cleaned": true,
"renderJs": true
}
}
}
Capture web page screenshots:
{
"name": "screenshot",
"arguments": {
"url": "https://example.com",
"width": 1280,
"height": 800,
"fullPage": true,
"format": "png",
"waitFor": 1000
}
}
Extract structured data using AI-powered instructions:
{
"name": "extract",
"arguments": {
"url": "https://example.com/products",
"instructions": "Extract all product names, prices, and descriptions from this page",
"schema": {
"products": [
{
"name": "string",
"price": "number",
"description": "string"
}
]
},
"renderJs": true
}
}
Convert documents to plaintext:
{
"name": "doc-to-text",
"arguments": {
"url": "https://example.com/document.pdf",
"options": {
"ocr": true,
"language": "en"
}
}
}
Convert files to PDF:
{
"name": "convert-to-pdf",
"arguments": {
"url": "https://example.com/document.docx",
"format": "docx",
"options": {
"quality": 90,
"pageSize": "A4",
"margin": 10
}
}
}
Merge multiple PDFs:
{
"name": "merge-pdfs",
"arguments": {
"urls": ["https://example.com/doc1.pdf", "https://example.com/doc2.pdf"],
"options": {
"addPageNumbers": true,
"addTableOfContents": true
}
}
}
Manage PDF metadata:
{
"name": "read-pdf-metadata",
"arguments": {
"url": "https://example.com/document.pdf",
"includeExtended": true
}
}
{
"name": "write-pdf-metadata",
"arguments": {
"url": "https://example.com/document.pdf",
"metadata": {
"title": "New Title",
"author": "John Doe",
"keywords": ["keyword1", "keyword2"]
}
}
}
Trim videos:
{
"name": "trim-video",
"arguments": {
"url": "https://example.com/video.mp4",
"startTime": 30,
"endTime": 60,
"output": "mp4",
"options": {
"quality": 720,
"fps": 30
}
}
}
Extract content from documents, images, audio, and video:
{
"name": "extract-document",
"arguments": {
"url": "https://example.com/document.pdf",
"format": "structured",
"options": {
"ocr": true,
"language": "en",
"includeMetadata": true
}
}
}
{
"name": "extract-image",
"arguments": {
"url": "https://example.com/image.jpg",
"extractionType": "text",
"options": {
"language": "en",
"detectOrientation": true
}
}
}
{
"name": "extract-audio",
"arguments": {
"url": "https://example.com/audio.mp3",
"language": "en",
"options": {
"model": "enhanced",
"speakerDiarization": true,
"wordTimestamps": true
}
}
}
{
"name": "extract-video",
"arguments": {
"url": "https://example.com/video.mp4",
"extractionType": "transcript",
"options": {
"language": "en",
"speakerDiarization": true
}
}
}
Generate responses using AI agents:
{
"name": "generate-agent-completion",
"arguments": {
"prompt": "How can I improve my website's SEO?",
"model": "gpt-4",
"temperature": 0.7,
"maxTokens": 500,
"context": ["The website is an e-commerce store selling handmade crafts."]
}
}
Search a knowledge base:
{
"name": "search-knowledge-base",
"arguments": {
"kbId": "kb_12345",
"query": "How to optimize database performance",
"limit": 5,
"similarityThreshold": 0.7
}
}
Add entries to a knowledge base:
{
"name": "add-to-knowledge-base",
"arguments": {
"kbId": "kb_12345",
"entries": [
{
"text": "MongoDB is a document-based NoSQL database.",
"metadata": {
"source": "MongoDB documentation",
"category": "databases"
}
}
],
"upsert": true
}
}
Generate AI images:
{
"name": "generate-ai-image",
"arguments": {
"prompt": "A futuristic city with flying cars and neon lights",
"width": 1024,
"height": 1024,
"numImages": 1,
"quality": "hd",
"style": "photorealistic"
}
}
{
"name": "generate-image",
"arguments": {
"prompt": "A golden retriever in a meadow of wildflowers",
"provider": "dalle",
"width": 1024,
"height": 1024,
"numImages": 1
}
}
Run JavaScript code with optional dependencies:
{
"name": "run-js-code",
"arguments": {
"code": "const result = [1, 2, 3, 4].reduce((sum, num) => sum + num, 0); console.log(`Sum: ${result}`); return result;",
"dependencies": {
"lodash": "^4.17.21"
},
"timeout": 5000
}
}
Run Python code with optional dependencies:
{
"name": "run-python-code",
"arguments": {
"code": "import numpy as np\narr = np.array([1, 2, 3, 4, 5])\nmean = np.mean(arr)\nprint(f'Mean: {mean}')\nreturn mean",
"dependencies": ["numpy", "pandas"],
"timeout": 10000,
"saveOutputFiles": true
}
}
The server provides detailed error messages with HTTP status codes. Here's an example error response:
{
"content": [
{
"type": "text",
"text": "Error: Failed to fetch YouTube transcript: 404 Not Found"
}
],
"isError": true
}
The error handling system includes:
To add this MCP server to Claude Code, run this command in your terminal:
claude mcp add-json "dumplingai" '{"command":"npx","args":["-y","mcp-server-dumplingai"],"env":{"DUMPLING_API_KEY":"<your-api-key>"}}'
See the official Claude Code MCP documentation for more details.
There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json
file so that it is available in all of your projects.
If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json
file.
To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".
When you click that button the ~/.cursor/mcp.json
file will be opened and you can add your server like this:
{
"mcpServers": {
"dumplingai": {
"command": "npx",
"args": [
"-y",
"mcp-server-dumplingai"
],
"env": {
"DUMPLING_API_KEY": "<your-api-key>"
}
}
}
}
To add an MCP server to a project you can create a new .cursor/mcp.json
file or add it to the existing one. This will look exactly the same as the global MCP server example above.
Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.
The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.
You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.
To add this MCP server to Claude Desktop:
1. Find your configuration file:
~/Library/Application Support/Claude/claude_desktop_config.json
%APPDATA%\Claude\claude_desktop_config.json
~/.config/Claude/claude_desktop_config.json
2. Add this to your configuration file:
{
"mcpServers": {
"dumplingai": {
"command": "npx",
"args": [
"-y",
"mcp-server-dumplingai"
],
"env": {
"DUMPLING_API_KEY": "<your-api-key>"
}
}
}
}
3. Restart Claude Desktop for the changes to take effect