How to Use the Microlink MCP in LangChain

Q: How do I register the Microlink tools inside a LangChain agent?

Install langchain-mcp-adapters and langgraph first. Initialize the MultiServerMCPClient with the server URL, call client.gettools(), and pass those tools directly to your agent constructor.

Feed live web data directly into your LangChain pipelines by converting any website into clean screenshots, metadata, or PDFs.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Microlink MCP to LangChain

Create your Vinkius account to connect Microlink to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Microlink with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain live web data with LangChain agents

`extract_metadata` serves as the starting point for your multi-step LangChain reasoning pipelines. Your AI client extracts structured JSON from target URLs and feeds that raw Microlink data directly into downstream chains. LangSmith traces every step of this Microlink data extraction. You see exact payload sizes and execution latencies inside your LangChain dashboard without guessing what broke.

Build visual verification steps in MCP Server workflows

`take_screenshot` captures pixel-perfect renders of target websites to verify UI changes during LangChain executions. The resulting Microlink image goes straight into your multimodal LLM chains for immediate visual analysis. This MCP Server setup lets your agent inspect specific viewport elements or emulate mobile devices using Microlink's engine. You run these visual verification steps sequentially within a single LangGraph state machine.

Generate structured documents on the fly

`generate_pdf` handles the heavy lifting of converting web pages into clean documents within your LangChain workflows. Your LangChain agent triggers this Microlink tool whenever a user requests an offline copy of a report. You configure Microlink margins, scale factors, and formats directly through the schema parameters. This eliminates the need for separate document generation microservices in your LangChain stack.

Setup guide

Set up Microlink MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Microlink tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "microlink-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Microlink transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Microlink. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Microlink now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Microlink MCP in LangChain

Install `langchain-mcp-adapters` and `langgraph` first. Initialize the `MultiServerMCPClient` with the server URL, call `client.get_tools()`, and pass those tools directly to your agent constructor.

Yes, it can. When your agent calls the PDF generation tool, the binary stream returns directly, letting you write the buffer to disk or feed it to another integration.

The server passes API headers directly to your client. If you hit rate limits, LangChain's built-in retry logic or your custom error handlers manage the backoff.

Custom scrapers break constantly when selectors change. This integration offloads browser maintenance, element selection, and device emulation to a single managed endpoint.

All target URLs and extracted metadata run inside ephemeral V8 isolates. Vinkius does not store the content of your requests, ensuring your proprietary web data remains private.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript