How to Use the AddSearch MCP in LangChain

Q: How do I connect AddSearch to LangChain?

Install the langchain-mcp-adapters package first. Then initialize a MultiServerMCPClient pointing to the Vinkius endpoint URL.

Q: Can my agent update the index?

Yes, agents can push new records using the indexdocument tool. They can also remove outdated entries via deletedocument if you give them the right permissions.

Q: Does this tool work with LangGraph?

It plugs right in. You just pass the MCP tools from client.gettools() into your node definitions.

Connect the AddSearch MCP Server to LangChain to build multi-step indexing chains and track search analytics via LangSmith.

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Connect AddSearch MCP to LangChain

Create your Vinkius account to connect AddSearch 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 AddSearch with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build ReAct Search Agents

Your LangChain agent needs to find specific content before making decisions. It calls `search_keyword` to grab initial hits, then dynamically follows up with `search_filtered` if the first batch returns too much noise. Every tool invocation logs straight to LangSmith. You see exactly how many tokens the agent burned while fetching `search_pagination` results.

Chain Document Operations with this MCP Server

Pipelines often require updating your search index after processing raw files. You can configure a sequence that processes PDF text and immediately passes the output to `index_document`. If a document gets flagged for removal, the next link in the chain triggers `delete_document`. The entire workflow runs autonomously based on your predefined logic.

Pipe Search Analytics into Dashboards

Sometimes you just need raw data on what users actually look for. A scheduled LangChain script can pull `stats_queries` and format the output into a weekly report. Adding `stats_clicks` into the same workflow lets the agent calculate conversion rates. It then drops that summary directly into your team's Slack channel.

Setup guide

Set up AddSearch 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 AddSearch 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({
    "addsearch-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 AddSearch 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 AddSearch. 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

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Common questions about AddSearch MCP in LangChain

Install the `langchain-mcp-adapters` package first. Then initialize a `MultiServerMCPClient` pointing to the Vinkius endpoint URL.

Yes, agents can push new records using the `index_document` tool. They can also remove outdated entries via `delete_document` if you give them the right permissions.

The agent will hit token limits quickly. You should prompt it to use `search_pagination` to handle large result sets in manageable chunks.

It plugs right in. You just pass the MCP tools from `client.get_tools()` into your node definitions.

Indexed site content and search queries stay isolated. The MCP connection runs inside a V8 sandbox that dies immediately after the session ends.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python