How to Use the Uniqode MCP in LangChain

Q: Can Uniqode track scan data across multiple campaigns with LangChain?

Absolutely. Your agent can first call listcampaigns to get all IDs, then loop through those results while calling getanalyticslocation for each one. This allows you to aggregate location trends from diverse marketing efforts into one cohesive output.

Q: If I need to check if a QR code needs updating, how do I use Uniqode with LangChain?

First, run getqrcode to pull the current details. Then, your agent can compare those details against what's available via listtags. If they don't match, it flags the need for an update using updateqrcode.

Build complex reasoning chains with LangChain: Connect Uniqode's tracking tools into multi-step agents.

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Connect Uniqode MCP to LangChain

Create your Vinkius account to connect Uniqode 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.

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Setup Uniqode with LangChain

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Deep Dive Scan Analysis

The `get_analytics_location` tool pulls scan data tied to a specific geographic area. You can then chain this output directly into the `get_analytics_time` tool. This sequence lets your agent determine exactly when and where most of your QR code scans happened. This is critical for operations teams needing proof points. An agent uses these two tools together, analyzing time-series data against location spikes, giving you a full picture that simple reporting can't touch.

Campaign Lifecycle Management

Need to manage multiple marketing efforts? Start by calling `list_campaigns` to get all active campaigns. Next, use the campaign ID to call `get_qrcode` and pull specific details on a target code. Your agent can then compare that data against what's listed using `list_tags`. This multi-step approach lets your system validate if a QR code is correctly tagged and linked to its intended campaign before deployment.

Organizational Resource Discovery

Before creating anything, check the scope. Use `list_organizations` to see which corporate units are involved. From there, an agent can call `list_folders` and then `list_qrcodes`. This ensures your multi-server MCP client has visibility into every folder structure. It's a structured way to build context. The chain validates that the target QR codes exist within the expected organizational hierarchy before attempting any updates.

Setup guide

Set up Uniqode 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 Uniqode 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({
    "uniqode-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 Uniqode transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Uniqode MCP in LangChain

LangChain excels at multi-step reasoning. You can set up a chain where the output of `list_campaigns` feeds directly into an agent that decides which specific QR code to analyze via `get_qrcode`. It doesn't just run tools; it makes them talk to each other.

Absolutely. Your agent can first call `list_campaigns` to get all IDs, then loop through those results while calling `get_analytics_location` for each one. This allows you to aggregate location trends from diverse marketing efforts into one cohesive output.

The MCP Server handles account details, campaign IDs, tag lists, and granular scan analytics (time/location). Your agent can process these different structured datasets to make informed decisions.

The server touches scan analytics data, which includes location and time stamps. The MCP Server handles this data type, allowing your AI client to process it within a secure, ephemeral sandbox.

First, run `get_qrcode` to pull the current details. Then, your agent can compare those details against what's available via `list_tags`. If they don't match, it flags the need for an update using `update_qrcode`.

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