Crawlbase 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 Crawlbase as an MCP tool provider through 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 Crawlbase. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Crawlbase?"
)
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 Crawlbase MCP Server
Connect your Crawlbase (formerly ProxyCrawl) account to any AI agent and take full control of your web scraping and anonymous crawling workflows through natural conversation.
LlamaIndex agents combine Crawlbase tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through 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
- Standard Scraper — Identify bounded routing spaces inside the headless engine to extract explicitly attached HTML content via datacenter proxies
- JS Rendering — Discover disconnected physical limits tracking exactly what JS-rendered frames expose to extract exact single-page UI bounds
- Structured JSON Extraction — Analyzes specific global bounds driving auto-extraction pipelines to force raw HTTP outputs into structured JSON format strictly
- Screenshot Capture — Dispatch automated validation checks to generate valid proxy endpoints returning configured Crawlbase screenshot URLs
- Specialized Scraping — Leverage dedicated algorithms for Amazon products, LinkedIn profiles, Facebook pages, and Twitter (X) graph profiles natively
- Search Engine Discovery — Explain explicitly mapped proxy lists targeting Google domains to parse SERP limits and bypass CAPTCHAs limitlessly
- Custom Proxy Management — Provision highly-available request payloads generating custom proxies with specific headers and crawling logic
The Crawlbase 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 Crawlbase to LlamaIndex via MCP
Follow these steps to integrate the Crawlbase 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 Crawlbase
Why Use LlamaIndex with the Crawlbase MCP Server
LlamaIndex provides unique advantages when paired with Crawlbase through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Crawlbase tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Crawlbase tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Crawlbase, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Crawlbase tools were called, what data was returned, and how it influenced the final answer
Crawlbase + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Crawlbase MCP Server delivers measurable value.
Hybrid search: combine Crawlbase real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Crawlbase 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 Crawlbase for fresh data
Analytical workflows: chain Crawlbase queries with LlamaIndex's data connectors to build multi-source analytical reports
Crawlbase MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Crawlbase to LlamaIndex via MCP:
custom_scrape
Provision a highly-available Request Payload generating Custom proxies
get_screenshot_link
Dispatch an automated validation check routing explicit Web Snapshot domains
scrape_amazon
Inspect deep internal arrays mitigating specific E-Commerce constraints
scrape_facebook
Enumerate explicitly attached structured rules exporting active Social Pages
scrape_google_serp
Identify precise active arrays spanning rented Context domains for Search
scrape_html
crawlbase.com` datacenter proxies. Identify bounded routing spaces inside the Headless Crawlbase Engine
scrape_js_rendered
Retrieve explicit Cloud logging tracing explicit Payload IDs limitlessly
scrape_json_format
Perform structural extraction of properties driving active Fields
scrape_linkedin
Retrieve the exact structural matching verifying Blueprint constraints
scrape_twitter
Fetch elaborate explicit mapped limits via Crawlbase X extraction
Example Prompts for Crawlbase in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Crawlbase immediately.
"Scrape the price and features from this Amazon product: [Amazon URL]"
"Get Google search results for 'best machine learning platforms 2024'"
"Take a screenshot of https://example.com"
Troubleshooting Crawlbase MCP Server with LlamaIndex
Common issues when connecting Crawlbase to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCrawlbase + LlamaIndex FAQ
Common questions about integrating Crawlbase 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 Crawlbase 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 Crawlbase to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.