Browse AI MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Browse AI 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({
"browse-ai-1": {
"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 Browse AI, 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 Browse AI MCP Server
Connect your Browse AI account to any AI agent and take full control of your no-code web scraping operations through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Browse AI 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
- Robot Discovery — List all your trained extraction and monitoring robots along with their configuration details
- Execute Scrapes — Trigger specific robots to run tasks on target URLs without lifting a finger
- Data Retrieval — Instantly download the final extracted JSON data from any successfully completed task
- Bulk Operations — Initiate multi-URL concurrent extractions and download the unified bulk datasets
- Monitor Sync — Check the status of your active web change monitors
- Quota Management — Retrieve your current API credits usage and monthly plan limits
The Browse AI 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 Browse AI to LangChain via MCP
Follow these steps to integrate the Browse AI 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 Browse AI via MCP
Why Use LangChain with the Browse AI MCP Server
LangChain provides unique advantages when paired with Browse AI through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Browse AI 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 Browse AI queries for multi-turn workflows
Browse AI + LangChain Use Cases
Practical scenarios where LangChain combined with the Browse AI MCP Server delivers measurable value.
RAG with live data: combine Browse AI tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Browse AI, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Browse AI tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Browse AI tool call, measure latency, and optimize your agent's performance
Browse AI MCP Tools for LangChain (10)
These 10 tools become available when you connect Browse AI to LangChain via MCP:
download_bulk_data
Returns a JSON array where each element contains the capturedData from one task. Download all extracted results from a completed Browse AI bulk run
get_bulk_task
Get bulk task execution status from Browse AI
get_robot
Get detailed configuration of a specific Browse AI robot
get_task
Check the status of a specific Browse AI extraction task
get_task_data
Only meaningful when the task status is "successful". Fields match the column names configured in the Browse AI robot builder hitting internal task references. Retrieve the final extracted JSON data from a successful Browse AI task
list_credits
Check Browse AI quota limits and credit usage
list_monitors
Monitors run on scheduled intervals to detect changes on target web pages and trigger notifications or data captures automatically via `/monitors`. List all active Browse AI web monitoring robots
list_robots
Each robot represents a no-code AI scraping workflow targeting a specific website or data pattern via `GET /robots`. List all Browse AI extraction and monitoring robots
run_bulk_task
Each set typically contains a different "originUrl". All extractions run concurrently on Browse AI infrastructure. Run a Browse AI robot in bulk mode across multiple URLs
run_robot
Pass a JSON string of input parameters (typically including "originUrl" for the target page and any variable fields the robot expects). Returns a taskId. Trigger a Browse AI robot to extract data from a target URL
Example Prompts for Browse AI in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Browse AI immediately.
"List all my robots. Which ones are built for monitoring?"
"Run my HackerNews Scraper robot on the main page."
"Retrieve the JSON data for task t-78ab31."
Troubleshooting Browse AI MCP Server with LangChain
Common issues when connecting Browse AI to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersBrowse AI + LangChain FAQ
Common questions about integrating Browse AI 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 Browse AI 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 Browse AI to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.