WebScrapingAPI MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add WebScrapingAPI as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to WebScrapingAPI. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in WebScrapingAPI?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About WebScrapingAPI MCP Server
Connect your WebScrapingAPI account to any AI agent and harness the power of industrial-grade web scraping through natural conversation.
LlamaIndex agents combine WebScrapingAPI tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Universal Scraping — Retrieve raw HTML from any website using a massive network of datacenter and residential proxies to avoid blocks
- JavaScript Rendering — Scrape complex SPAs and dynamic pages by using a headless browser to capture the full rendered state
- SERP Discovery — Retrieve structured search engine results (organic, ads, snippets) from Google, Bing, and Yandex
- E-commerce Extraction — Scrape product details like price, reviews, and titles from major stores like Amazon and Walmart into structured JSON
- Anonymity & Bypass — Use residential or mobile proxies for high-anonymity scraping and to bypass even the most aggressive bot detections
- Auto-Parsing — Automatically extract structured data from news articles or product pages without manual selectors
- Custom Parameters — Execute scrapes with advanced options like geo-targeting, sessions, and custom headers
The WebScrapingAPI MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect WebScrapingAPI to LlamaIndex via MCP
Follow these steps to integrate the WebScrapingAPI MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from WebScrapingAPI
Why Use LlamaIndex with the WebScrapingAPI MCP Server
LlamaIndex provides unique advantages when paired with WebScrapingAPI through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine WebScrapingAPI tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain WebScrapingAPI tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query WebScrapingAPI, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what WebScrapingAPI tools were called, what data was returned, and how it influenced the final answer
WebScrapingAPI + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the WebScrapingAPI MCP Server delivers measurable value.
Hybrid search: combine WebScrapingAPI real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query WebScrapingAPI to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying WebScrapingAPI for fresh data
Analytical workflows: chain WebScrapingAPI queries with LlamaIndex's data connectors to build multi-source analytical reports
WebScrapingAPI MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect WebScrapingAPI to LlamaIndex via MCP:
custom_api_scrape
g. country, session, wait_for). Execute a scrape using advanced custom parameters
scrape_and_auto_extract
g. for news or product pages). Scrape with automatic structured data extraction
scrape_as_mobile
Scrape as a mobile device using WebScrapingAPI device emulation
scrape_ecommerce_product
Returns price, title, and reviews as structured JSON. Scrape product details from Amazon, Walmart, or other supported stores
scrape_js_rendered
Slower but captures the full rendered state. Scrape JS-rendered HTML using WebScrapingAPI headless browser
scrape_static_html
Pass the full target URL. Scrape raw HTML from any URL using WebScrapingAPI datacenter proxies
scrape_via_residential_proxy
Scrape using residential proxies for high anonymity and bypass
search_bing_serp
Retrieve structured search engine results from Bing
search_google_serp
Provide a query string. Retrieve structured search engine results from Google
search_yandex_serp
Retrieve structured search engine results from Yandex
Example Prompts for WebScrapingAPI in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with WebScrapingAPI immediately.
"Scrape the rendered HTML of 'https://example.com/dynamic-dashboard'."
"Search Google for 'best wireless noise cancelling headphones' and return structured results."
"Get the price and rating for the product at 'https://amazon.com/dp/B09XXX'."
Troubleshooting WebScrapingAPI MCP Server with LlamaIndex
Common issues when connecting WebScrapingAPI to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpWebScrapingAPI + LlamaIndex FAQ
Common questions about integrating WebScrapingAPI MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect WebScrapingAPI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect WebScrapingAPI to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.