AdRoll MCP Server for LangChain 5 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect AdRoll 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({
"adroll": {
"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 AdRoll, 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 AdRoll MCP Server
Connect your AdRoll (NextRoll) account to your AI agent to unlock professional e-commerce marketing and retargeting orchestration. From auditing your advertisable accounts to monitoring real-time campaign performance and managing creative ad assets, your agent handles your advertising ecosystem through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with AdRoll through native MCP adapters. Connect 5 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
- Campaign Management — List and retrieve details for active campaigns across multiple channels (Web, Facebook, etc.)
- Account Auditing — List your 'Advertisables' (advertiser accounts) and retrieve technical metadata for each
- Performance Reporting — Retrieve granular statistics on clicks, spend, and conversions to monitor your marketing ROI
- Creative Asset Oversight — List and audit your ad creatives (banners, videos) to ensure your visual content is optimized
- Strategy Insights — Quickly identify high-performing strategies and identify areas for budget optimization directly from chat
The AdRoll MCP Server exposes 5 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 AdRoll to LangChain via MCP
Follow these steps to integrate the AdRoll 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 5 tools from AdRoll via MCP
Why Use LangChain with the AdRoll MCP Server
LangChain provides unique advantages when paired with AdRoll through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine AdRoll 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 AdRoll queries for multi-turn workflows
AdRoll + LangChain Use Cases
Practical scenarios where LangChain combined with the AdRoll MCP Server delivers measurable value.
RAG with live data: combine AdRoll tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query AdRoll, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain AdRoll tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every AdRoll tool call, measure latency, and optimize your agent's performance
AdRoll MCP Tools for LangChain (5)
These 5 tools become available when you connect AdRoll to LangChain via MCP:
get_campaign_details
Get campaign metadata
get_performance_report
Filterable by EID and date. Get performance statistics
list_ads
List ad creatives
list_advertisables
List advertiser accounts
list_campaigns
List active campaigns
Example Prompts for AdRoll in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with AdRoll immediately.
"List all active advertisable accounts in my AdRoll organization."
"Show me the performance of my Web Retargeting campaign for the last 7 days."
"List all ad creatives for advertisable EID 'AD1234567890'."
Troubleshooting AdRoll MCP Server with LangChain
Common issues when connecting AdRoll to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersAdRoll + LangChain FAQ
Common questions about integrating AdRoll 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 AdRoll 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 AdRoll to LangChain
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.
