How to Use the Vertex AI Search MCP in LangChain

Q: Can I use Vertex AI Search with LangChain to find specific documents?

Yes. You can list all indexed documents using listdatastoredocuments after specifying both the data store and branch IDs. This lets your agent confirm if the information you need is actually present.

Q: Does the MCP Server support structured API calls for LangChain?

Absolutely. The server exposes clear tools like listsearchengines, letting your agent list and interact with all configured search engines in the collection.

Q: How can I check which data stores are available via Vertex AI Search and LangChain?

You start by calling listdatastores. This function provides a quick, comprehensive list of every single data store that's ready for your agent to use.

Build reasoning pipelines using LangChain's agentic capabilities.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Vertex AI Search MCP to LangChain

Create your Vinkius account to connect Vertex AI Search 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.

GDPR Free for Subscribers

Setup Vertex AI Search with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-step search via the MCP Server

When you call `search_documents`, your agent executes a query across documents in a specific data store. This is the starting point for complex searches. Later, if you need personalized context, use `get_recommendations`. Your agent can chain these two calls—first searching general knowledge, then refining that search with user-specific recommendations.

Getting grounded answers

The tool `get_grounded_answer` returns a natural language response based on your private data. Instead of just giving links, it synthesizes an answer directly from the source documents. It's perfect for agents that need to write up reports or summaries. The agent calls this function and immediately gets a vetted answer backed by your enterprise knowledge.

Managing data sources

Need to know what data stores you're working with? `list_data_stores` gives you a complete inventory of everything indexed. You can then use `get_datastore_details` to pull specific metadata and configuration for any store. This is how your agent figures out which source it needs to query next, keeping the chain moving without manual input.

Setup guide

Set up Vertex AI Search 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 Vertex AI Search 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({
    "vertex-ai-search-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 Vertex AI Search transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

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

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Vertex AI Search now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Vertex AI Search MCP in LangChain

LangChain uses this MCP Server to build multi-step reasoning. Your agent decides which tool—like `search_documents` or `get_grounded_answer`—to call and in what order, treating the output of one as input for the next.

Yes. You can list all indexed documents using `list_datastore_documents` after specifying both the data store and branch IDs. This lets your agent confirm if the information you need is actually present.

It handles documents, allowing your agent to run a query across them using `search_documents`. It also processes user event data when running `get_recommendations`.

Absolutely. The server exposes clear tools like `list_search_engines`, letting your agent list and interact with all configured search engines in the collection.

You start by calling `list_data_stores`. This function provides a quick, comprehensive list of every single data store that's ready for your agent to use.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript