# mcp-server [Health: Active] **Category:** 🌐 Social Media **Repository:** https://github.com/Decodo/mcp-server **GitHub Stars:** 34 **Views:** 1 **Installs:** 0 **Upvotes:** 0 **Directory Page:** https://allmcps.com/mcp/mcp-server-64 ## Description Enable your AI agents to scrape and parse web content dynamically, including geo-restricted sites ## Tools Capabilities this server exposes over MCP: - **scrape_as_markdown** — Scrapes any target URL, expects a URL to be given via prompt. Returns results in Markdown. - **screenshot** — Captures a screenshot of any webpage and returns it as a PNG image. - **google_search** — Scrapes Google Search for a given query, and returns parsed results. - **google_ads** — Scrapes Google Ads search results. - **google_lens** — Scrapes Google Lens image search results. - **google_ai_mode** — Scrapes Google AI Mode (Search with AI) results. - **google_travel_hotels** — Scrapes Google Travel Hotels search results. - **amazon_search** — Scrapes Amazon Search for a given query, and returns parsed results. - **amazon_product** — Scrapes Amazon Product page. - **amazon_pricing** — Scrapes Amazon Product pricing information. - **amazon_sellers** — Scrapes Amazon Seller information. - **amazon_bestsellers** — Scrapes Amazon Bestsellers list. - **walmart_search** — Scrapes Walmart Search for a given query, and returns parsed results. - **walmart_product** — Scrapes Walmart Product page. - **target_search** — Scrapes Target Search for a given query, and returns parsed results. - **target_product** — Scrapes Target Product page. - **tiktok_post** — Scrapes a TikTok post URL for structured data (e.g. engagement, caption, hashtags). - **tiktok_shop_search** — Scrapes TikTok Shop Search for a given query, and returns parsed results. - **tiktok_shop_product** — Scrapes TikTok Shop Product page. - **tiktok_shop_url** — Scrapes TikTok Shop page by URL. - **youtube_metadata** — Scrapes YouTube video metadata. - **youtube_channel** — Scrapes YouTube channel videos. - **youtube_subtitles** — Scrapes YouTube video subtitles. - **youtube_search** — Search YouTube videos. - **reddit_post** — Scrapes a specific Reddit post. - **reddit_subreddit** — Scrapes Reddit subreddit results. - **reddit_user** — Scrapes a Reddit user profile and their posts/comments. - **bing_search** — Scrapes Bing Search results. - **chatgpt** — Search and interact with ChatGPT for AI-powered responses and conversations. - **perplexity** — Search and interact with Perplexity for AI-powered responses and conversations. ## Claude Desktop Quick Installation Install path detected from listing signals. Uses `npx` (confidence: high): ```json "mcpServers": { "mcp-server": { "command": "npx", "args": ["-y","@decodo/mcp-server"] } } ``` ## Documentation & README # Decodo MCP Server [![](https://dcbadge.limes.pink/api/server/https://discord.gg/Ja8dqKgvbZ)](https://discord.gg/Ja8dqKgvbZ) [![Install MCP Server](https://cursor.com/deeplink/mcp-install-dark.svg)](https://cursor.com/en-US/install-mcp?name=Decodo&config=eyJ1cmwiOiJodHRwczovL21jcC5kZWNvZG8uY29tL21jcCIsImhlYWRlcnMiOnsiQXV0aG9yaXphdGlvbiI6IkJhc2ljIDx3ZWJfYWR2YW5jZWRfdG9rZW4%2BIn19)

Connect LLMs and AI agents to live web data using MCP (Model Context Protocol). The Decodo MCP Server lets you scrape websites, search engines, eCommerce platforms, and social media directly from AI tools like Claude, Cursor, and Windsurf, all without the need to build scraping infrastructure from scratch. - Structured outputs in JSON, Markdown, and screenshots - Server-side JavaScript rendering and anti-bot handling - 125M+ IPs across 195+ locations ## What is Decodo MCP server? The Decodo MCP Server is a web scraping layer for AI agents. It connects MCP-compatible clients to Decodo's Web Scraping API, enabling: - Web scraping for LLMs - Real-time data retrieval for RAG - AI agent browsing and research - Structured data extraction from dynamic websites Instead of maintaining proxies, parsers, and retry logic, you get a single integration point for reliable web data access. ## Why use MCP for web scraping? Model Context Protocol (MCP) is the emerging standard for connecting AI agents to external tools and data sources. With MCP: - Agents can call tools dynamically - Integrations stay standardized - Workflows scale across environments The Decodo MCP Server gives your agents reliable, production-ready web access through this standard. ## Key features **Web scraping for AI agents, no infrastructure required.** Scrape any website, including JavaScript-heavy pages, without handling proxy rotation, CAPTCHA solving, or anti-bot systems. **Structured outputs for LLM workflows.** Markdown (LLM-ready), JSON (for structured pipelines), and screenshots (for visual context), built for RAG pipelines, AI research agents, and automation flows. **Built-in support for popular targets.** Ready-made tools for Google and Bing (SERPs), Amazon, Walmart, and Target (eCommerce), Reddit, TikTok, and YouTube (social media), and ChatGPT and Perplexity (AI search). **Global proxy infrastructure.** 125M+ residential IPs, 195+ geo-locations, and a 99.99% success rate on even the most protected targets. **Modular MCP toolsets.** Enable only what you need: `web`, `search`, `ecommerce`, `social_media`, `ai` for cleaner tool selection and better agent performance. **Fast time to value.** From API key to first scrape in minutes, no setup overhead. ## Use cases Use the Decodo MCP Server when you need web scraping for AI agents, structured data extraction at scale, reliable access to dynamic websites, real-time data for RAG, or an alternative to building scraping infrastructure from scratch. Common scenarios: - **AI-powered web scraping** – give LLMs the ability to collect fresh data instead of relying on static training data. - **RAG with live data** – pull real-time Google, Bing, and AI search results into retrieval pipelines. - **eCommerce intelligence** – track product prices, listings, and sellers across marketplaces without getting blocked. - **Social media data collection** – gather posts, channels, and engagement data from Reddit, TikTok, and YouTube. - **Travel and price aggregation** – build tools that collect live pricing and availability across websites. ## Quick start 1. **Create a free account** at [dashboard.decodo.com](https://dashboard.decodo.com/) – up to 2K free requests, no credit card required. 2. **Get your API key.** Obtain a Web Scraping API basic authentication token from the dashboard. 3. **Download Node.js 18+** from https://nodejs.org. 4. **Get MCP client** like Claude Desktop, Curson, Windsurf or other MCP-compatible tools.. 5. **Configure the MCP server** in your AI client (see configuration examples below). ## Connecting to [Decodo's MCP server](https://mcp.decodo.com/mcp) Open your preferred MCP client and add the following configuration (see examples for Claude Code, Cursor, Windsurf bellow): ``` { "mcpServers": { "Decodo": { "url": "https://mcp.decodo.com/mcp", "headers": { "Authorization": "Basic " } } } } ``` ### Claude Desktop 1. Open Claude Desktop → Settings → Developer → Edit Config. 2. Add to claude_desktop_config.json: ``` { "mcpServers": { "Decodo": { "command": "npx", "args": ["-y", "@decodo/mcp-server"], "env": { "SCRAPER_API_TOKEN": "", "TOOLSETS": "web,ai" } } } } ``` 3. Save and restart Claude Desktop. ### Cursor 1. Open Settings → MCP. 2. Click Add a new global MCP server (opens mcp.json). 3. Add the same configuration as above. 4. Save — look for a green status indicator next to Decodo. ### Windsurf 1. Open Settings → Windsurf Settings. 2. Scroll to Cascade → Add custom server + (opens mcp_config.json). 3. Add the same configuration as above. 4. Save and restart Windsurf. ## Test your setup Once connected, try this prompt in your client: ▎ "Scrape the titles of the top 5 articles from Hacker News" You should get a structured list back within seconds. If you see an auth error, double-check your token from the dashboard. ## Optional: enable specific toolsets # Running the MCP server locally

### Prerequisites - Node.js 18.0+ - An MCP client - popular choices are [Claude Desktop](https://claude.ai/download) and [Cursor](https://www.cursor.com/) ### Step-by-step guide 1. Clone this repository: ``` git clone https://github.com/Decodo/mcp-server ``` 2. Run the following commands in the terminal: ``` cd decodo-mcp-server npm install npm run build ``` 3. Take note of your build location: ``` cd build/ pwd ``` Adding `index.js` to the end of this directory, your build file location should look something like this: ``` /Users/your.user/projects/decodo-mcp/build/index.js ``` 4. Update your MCP client with the server information: ``` { "mcpServers": { "decodo-mcp": { "command": "node", "args": ["/Users/your.user/projects/decodo-mcp/build/index.js"], "env": { "SCRAPER_API_TOKEN": "" } } } } ```
## Toolsets Tools are organized into toolsets. You can selectively enable specific toolsets by passing a comma-separated list via the `toolsets` query parameter: ``` "Decodo MCP Server": { "url": "https://mcp.decodo.com/mcp?toolsets=web,ai", "headers": { "Authorization": "Basic " } } ``` When no toolsets are specified, all tools are registered. | Toolset | Tools | | -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `web` | `scrape_as_markdown`, `screenshot` | | `search` | `google_search`, `google_ads`, `google_lens`, `google_travel_hotels`, `bing_search` | | `ecommerce` | `amazon_search`, `amazon_product`, `amazon_pricing`, `amazon_sellers`, `amazon_bestsellers`, `walmart_search`, `walmart_product`, `target_search`, `target_product`, `tiktok_shop_search`, `tiktok_shop_product`, `tiktok_shop_url` | | `social_media` | `reddit_post`, `reddit_subreddit`, `reddit_user`, `tiktok_post`, `youtube_metadata`, `youtube_channel`, `youtube_subtitles`, `youtube_search` | | `ai` | `chatgpt`, `perplexity`, `google_ai_mode` | ## Tools The server exposes the following tools: | Tool | Description | Example prompt | | ---------------------- | ------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------- | | `scrape_as_markdown` | Scrapes any target URL, expects a URL to be given via prompt. Returns results in Markdown. | Scrape peacock.com from a US IP address and tell me the pricing. | | `screenshot` | Captures a screenshot of any webpage and returns it as a PNG image. | Take a screenshot of github.com from a US IP address. | | `google_search` | Scrapes Google Search for a given query, and returns parsed results. | Scrape Google Search for shoes and tell me the top position. | | `google_ads` | Scrapes Google Ads search results. | Scrape Google Ads for laptop and show me the top ads. | | `google_lens` | Scrapes Google Lens image search results. | Search Google Lens for this image: https://example.com/image.jpg | | `google_ai_mode` | Scrapes Google AI Mode (Search with AI) results. | Ask Google AI Mode: What are the top three dog breeds? | | `google_travel_hotels` | Scrapes Google Travel Hotels search results. | Search Google Travel Hotels for hotels in Paris. | | `amazon_search` | Scrapes Amazon Search for a given query, and returns parsed results. | Scrape Amazon Search for wireless keyboard. | | `amazon_product` | Scrapes Amazon Product page. | Scrape Amazon product B09H74FXNW and show me the details. | | `amazon_pricing` | Scrapes Amazon Product pricing information. | Get pricing for Amazon product B09H74FXNW. | | `amazon_sellers` | Scrapes Amazon Seller information. | Get information about Amazon seller A1R0Z7FJGTKESH. | | `amazon_bestsellers` | Scrapes Amazon Bestsellers list. | Show me Amazon bestsellers in electronics. | | `walmart_search` | Scrapes Walmart Search for a given query, and returns parsed results. | Scrape Walmart Search for camping tent. | | `walmart_product` | Scrapes Walmart Product page. | Scrape Walmart product 15296401808. | | `target_search` | Scrapes Target Search for a given query, and returns parsed results. | Scrape Target Search for kitchen appliances. | | `target_product` | Scrapes Target Product page. | Scrape Target product 92186007. | | `tiktok_post` | Scrapes a TikTok post URL for structured data (e.g. engagement, caption, hashtags). | Scrape this TikTok post: https://www.tiktok.com/@nba/video/7393013274725403950 | | `tiktok_shop_search` | Scrapes TikTok Shop Search for a given query, and returns parsed results. | Scrape TikTok Shop Search for phone cases. | | `tiktok_shop_product` | Scrapes TikTok Shop Product page. | Scrape TikTok Shop product 1731541214379741272. | | `tiktok_shop_url` | Scrapes TikTok Shop page by URL. | Scrape this TikTok Shop URL: https://www.tiktok.com/shop/s?q=HEADPHONES | | `youtube_metadata` | Scrapes YouTube video metadata. | Get metadata for YouTube video dFu9aKJoqGg. | | `youtube_channel` | Scrapes YouTube channel videos. | Scrape YouTube channel @decodo_official. | | `youtube_subtitles` | Scrapes YouTube video subtitles. | Get subtitles for YouTube video L8zSWbQN-v8. | | `youtube_search` | Search YouTube videos. | Search YouTube for "How to care for chinchillas". | | `reddit_post` | Scrapes a specific Reddit post. | Scrape the following Reddit post: https://www.reddit.com/r/horseracing/comments/1nsrn3/ | | `reddit_subreddit` | Scrapes Reddit subreddit results. | Scrape the top 5 posts on r/Python this week. | | `reddit_user` | Scrapes a Reddit user profile and their posts/comments. | Scrape this Reddit user: https://www.reddit.com/user/IWasRightOnce/ | | `bing_search` | Scrapes Bing Search results. | Search Bing for laptop reviews. | | `chatgpt` | Search and interact with ChatGPT for AI-powered responses and conversations. | Ask ChatGPT to explain quantum computing in simple terms. | | `perplexity` | Search and interact with Perplexity for AI-powered responses and conversations. | Ask Perplexity what the latest trends in web development are. | ## Parameters The following parameters are inferred from user prompts: | Parameter | Description | | --------------- | ----------------------------------------------------------------------------------------------------- | | `jsRender` | Renders target URL in a headless browser. | | `geo` | Sets the country from which the request will originate. | | `locale` | Sets the locale of the request. | | `tokenLimit` | Truncates the response content up to this limit. Useful if the context window is small. | | `prompt` | Prompt to send to AI tools (`chatgpt`, `perplexity`). | | `search` | Activates ChatGPT's web search functionality (`chatgpt` only). | | `xhr` | When true, includes XHR or fetch responses in the scrape result where supported (e.g. `tiktok_post`). | | `deviceType` | Device type to emulate for the request (`desktop`, `mobile`, `tablet`). | | `domain` | Domain to use for the request (e.g., `amazon.com`, `amazon.co.uk`, `bing.com`). | | `pageFrom` | Starting page number for pagination. | | `deliveryZip` | ZIP code for delivery location (Target, Walmart). | | `storeId` | Store ID for local inventory (Target, Walmart). | | `country` | Country for TikTok Shop requests. | | `limit` | Maximum number of results to return (e.g., YouTube channel videos). | | `language_code` | Language code for subtitles (e.g., `en`, `es`). | ## Examples ### Scraping geo-restricted content Query your AI agent with the following prompt: ``` Scrape peacock.com from a German IP address and tell me the pricing. ``` This prompt will say that peacock.com is geo-restricted. To bypass the geo-restriction: ``` Scrape peacock.com from a US IP address and tell me the pricing. ``` ### Limiting number of response tokens If your agent has a small context window, the content returned from scraping will be automatically truncated, in order to avoid context-overflow. You can increase the number of tokens returned within your prompt: ``` Scrape hacker news, return 50k tokens. ``` If your agent has a big context window, tell it to return `full content`: ``` Scrape hacker news, return full content. ``` ## Use with Decodo agent skills This server gives your agent the scraping *tools*. [`Decodo/agent-skills`](https://github.com/Decodo/agent-skills) teaches it **when** to reach for them, **which** surface to use, and **how** to call it — so the agent picks the right tool and parameters on its own instead of guessing. The skills route across the `decodo` CLI, this hosted MCP server, and the raw HTTP API, and fall back to the MCP server automatically when no shell is available. Pairing the two gives your agent both the execution layer (this server) and the decision layer (the skills) in a single setup. **Quick start** (Claude Code): ```text /plugin marketplace add Decodo/agent-skills /plugin install decodo@decodo-skills ``` See the [agent-skills README](https://github.com/Decodo/agent-skills#readme) for manual install and other agents (Cursor, Codex, Gemini CLI, Windsurf). ## Related repositories [Web Scraping API](https://github.com/Decodo/Web-Scraping-API), [Decodo agent skills](https://github.com/Decodo/agent-skills), [Decodo OpenClaw skill](https://github.com/Decodo/decodo-openclaw-skill) ## Try it Plug Decodo MCP Server into your AI workflow in just a few clicks and equip your AI agents with real-time data from any website. [Start for free](https://dashboard.decodo.com/) | [Docs](https://help.decodo.com/docs/introduction) | [Discord](https://discord.gg/Ja8dqKgvbZ) ## License All code is released under the [MIT License](https://github.com/Decodo/Decodo/blob/master/LICENSE).