How to Use the Expansify AI MCP in LangChain

Q: Can LangChain agents run multiple Expansify AI tools in a single run?

Yes. You can build chains that run analyzekeywordseo first, evaluate the metrics, and then trigger createcampaign based on the results.

Q: Can I combine the Expansify AI MCP Server with vector stores in LangChain?

Yes. You can fetch your active marketing runs using listcampaigns and store the metadata in a vector database for long-term retrieval.

Run automated marketing pipelines where your LangChain agents build campaigns and write SEO-backed content in one continuous chain.

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Connect Expansify AI MCP to LangChain

Create your Vinkius account to connect Expansify AI 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 Expansify AI with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-step SEO content chains in LangChain

Your agent runs `analyze_keyword_seo` to grab search volume and immediately pipes those insights into `generate_ai_content`. Letting LangChain handle the sequence means you don't copy-paste data between tools. The output of your SEO analysis feeds directly into your content writer, keeping your search intent completely aligned. We don't do guesswork here.

Trace campaign execution with LangSmith

This MCP Server connects to your LangChain setup, letting you audit how `create_campaign` runs under the hood. Stop guessing why your agent wrote a specific post or picked a weird keyword. You get clear visibility into how `list_campaigns` runs. If a generated draft misses the mark, you can pinpoint the exact step in the chain that went off course.

Build autonomous marketing agents

Your ReAct agent checks your performance by running `list_tracked_keywords` to identify where you are losing ground. Go beyond simple scripts and let agents decide how to distribute your content. It can automatically trigger `create_campaign` and write fresh drafts using `list_generated_content` as context. You set the goal, and the agent uses the MCP tools to handle the execution.

Setup guide

Set up Expansify AI 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 Expansify AI 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({
    "expansify-ai-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 Expansify AI 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 Expansify AI. 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 Expansify AI MCP in LangChain

Install the langchain-mcp-adapters package and initialize the MultiServerMCPClient using your Vinkius transport URL. Once connected, fetch the tools and pass them directly to your agent executor.

Yes. You can build chains that run `analyze_keyword_seo` first, evaluate the metrics, and then trigger `create_campaign` based on the results.

LangChain handles rate limits through standard runnable retry configurations. If `generate_ai_content` hits an API ceiling, the chain pauses and retries automatically.

Yes. You can fetch your active marketing runs using `list_campaigns` and store the metadata in a vector database for long-term retrieval.

Your marketing copy and campaign metadata never persist on the Vinkius proxy. Every call to `list_generated_content` runs in an isolated sandbox that wipes your data immediately after the chain completes.

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