How to Use the Amazon DSP MCP in LangChain

Build multi-step ReAct agents that sequence Amazon DSP campaign data directly into your LangChain pipelines.

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Connect Amazon DSP MCP to LangChain

Create your Vinkius account to connect Amazon DSP 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 Amazon DSP with LangChain

Ask AI about this MCP

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Claude

Perplexity

Tie this MCP Server to LangChain ReAct agents

Give your reasoning agent direct access to programmatic ad structures. When you connect the server, the agent pulls active flights using `list_campaigns` and immediately maps the underlying structures via `list_ad_groups`. It decides what to pull based on the previous step's output. You get full observability through LangSmith. Every API call shows up in your trace logs, detailing exactly how long the MCP integration took to fetch the data and what tokens it burned parsing the platform response.

Sequence performance reports

Stop manually checking campaign metrics. Your chain can fire off a `request_report` call, wait out the processing delay, and loop `get_report_status` until the data is actually ready for extraction. Once the report drops, the agent grabs the output and feeds it into your next node. You might pipe that raw performance data into a vector store or run it through an LLM to summarize weekly spend.

Map audiences to creative assets

Complex campaigns require tight alignment between who you target and what they see. A multi-step chain pulls your segments via `list_audiences` and cross-references them with available assets using `list_creatives`. The agent handles the relationships automatically. If a specific creative is missing for a high-value audience, the MCP protocol allows the chain to trigger an alert or draft a request for the design team.

Setup guide

Set up Amazon DSP 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 Amazon DSP 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({
    "amazon-dsp-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 Amazon DSP transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Amazon DSP. 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.

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Common questions about Amazon DSP MCP in LangChain

Install the adapters package. Initialize a multi-server client pointing to your Vinkius endpoint, call the tool extraction method, and pass the array to your agent constructor.

Yes. The agent chains the request command to generate the file, then loops the status check until completion. You control the retry logic directly in your graph.

Every single execution gets logged. You see the exact inputs sent to the MCP Server and the raw JSON response returned by the ad platform.

ReAct agents handle this natively. The output from a campaign list operation automatically becomes the input argument when the agent decides to fetch deeper ad group details.

Vinkius runs the server in an ephemeral V8 Isolate sandbox. Your audience segments and creative metadata pass directly to your local execution environment. We tear down the sandbox the millisecond the request finishes.

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