AdRoll MCP Server for LangChainGive LangChain instant access to 7 tools to Get Campaign, Get Report, List Adgroups, and more
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 App Connector for LangChain
The AdRoll app connector for LangChain is a standout in the Marketing Automation category — giving your AI agent 7 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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-alternative": {
"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 account to any AI agent and take full control of your digital advertising operations and retargeting workflows through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with AdRoll through native MCP adapters. Connect 7 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 Orchestration — List and manage all your advertising campaigns programmatically, retrieving detailed budget settings and high-fidelity operational status in real-time
- Ad Group & Creative Intelligence — Access your complete directory of ad groups and creative assets to coordinate your visual marketing strategy across multiple channels
- Performance Reporting — Programmatically retrieve real-time metrics including clicks, impressions, and high-fidelity spend data to optimize your ROI directly through your agent
- Audience Segmentation — Access and manage your retargeting segments to ensure perfectly coordinated audience targeting and high-fidelity personalized experiences
- Infrastructure Monitoring — Access advertisable profile metadata and verify account-level settings directly through your agent for instant operational reporting
The AdRoll MCP Server exposes 7 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.
All 7 AdRoll tools available for LangChain
When LangChain connects to AdRoll through Vinkius, your AI agent gets direct access to every tool listed below — spanning retargeting, performance-marketing, ad-campaigns, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Get campaign details
Pass report criteria as a JSON string. Get performance report
List ad groups for a campaign
List all ads for an advertisable
List all advertisable profiles
List campaigns for an advertisable
List audience segments
Connect AdRoll to LangChain via MCP
Follow these steps to wire AdRoll into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
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
Example Prompts for AdRoll in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with AdRoll immediately.
"List all my active advertising campaigns for profil EID '123'."
"Show the performance report (clicks and spend) for last week."
"List the audience segments for advertisable '123'."
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.