How to Use the Moloco MCP in LangChain

Q: Can I automate my Moloco budget decisions using LangChain?

Yes, you can build a chain that checks getaccountbalance and getanalyticsreport before deciding to update status. The agent handles the decision logic based on the data provided.

Chain your Moloco ad-ops directly into LangChain pipelines for automated, multi-step performance optimization.

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Connect Moloco MCP to LangChain

Create your Vinkius account to connect Moloco 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 Moloco with LangChain

Ask AI about this MCP

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Claude

Perplexity

Chain Ad-Ops with Moloco MCP

Feed your performance data from `get_analytics_report` directly into complex reasoning chains. You define how the output of one step determines the next action without manual intervention. Your agent parses the data, evaluates current spend, and prepares the logic for the next chain link. It keeps your workflow moving by automating the flow of information between disparate tasks.

Automated Status Control

Trigger `update_campaign_status` based on your custom chain criteria. Your agent monitors results and shifts campaign states as soon as performance thresholds are met. This removes the delay between analysis and execution. You get immediate control over your ad presence using the tools provided by this MCP Server.

Deep Observability Integration

Trace every tool call within your LangSmith logs to see exactly how your agent handles Moloco data. Every input and output is captured for review. This ensures you know exactly why a change was made to your account. You can debug your agent’s logic by looking at the raw data returned by `list_campaigns` and other endpoints.

Setup guide

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

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Common questions about Moloco MCP in LangChain

You connect by using the MCP adapters to define your server transport. Once the client is initialized, you pass the tool list into your agent constructor to start executing commands.

Yes, you can build a chain that checks `get_account_balance` and `get_analytics_report` before deciding to update status. The agent handles the decision logic based on the data provided.

The server uses a single endpoint token for authentication and operates within a zero-trust sandbox. Your API credentials stay isolated from your agent's general processing environment.

It does. You can aggregate multiple servers alongside this one to give your agent access to more data sources simultaneously.

Only the specific performance and campaign data requested by your agent is retrieved. This MCP Server does not store your account information, ensuring your raw data remains ephemeral.

Use it with your favorite AI tools

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

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