Crawlbase MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Crawlbase through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"crawlbase": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Crawlbase, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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.
LangChain's ecosystem of 500+ components combines seamlessly with Crawlbase through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the Crawlbase MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from Crawlbase via MCP
Why Use LangChain with the Crawlbase MCP Server
LangChain provides unique advantages when paired with Crawlbase through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Crawlbase MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Crawlbase queries for multi-turn workflows
Crawlbase + LangChain Use Cases
Practical scenarios where LangChain combined with the Crawlbase MCP Server delivers measurable value.
RAG with live data: combine Crawlbase tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Crawlbase, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Crawlbase tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Crawlbase tool call, measure latency, and optimize your agent's performance
Crawlbase MCP Tools for LangChain (10)
These 10 tools become available when you connect Crawlbase to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting Crawlbase to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersCrawlbase + LangChain FAQ
Common questions about integrating Crawlbase MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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 LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.