How to Use the Wasabi MCP in LangChain

Q: How do I check bucket metadata with Wasabi and LangChain?

You use getbucketdatacenterlocation to get the physical region. This single tool call returns the precise geographic area where the data is housed, letting your agent ground its decisions in concrete facts.

Q: Can LangChain manage object access control with Wasabi?

Yep. You run getobjectaccesscontrol to pull the specific ACL for any file you care about. This gives your agent visibility into who has permission to read or write that data.

Q: If I want to list all my buckets using Wasabi and LangChain?

Just call liststoragebuckets. This tool immediately returns a comprehensive list of every bucket visible to the authenticated IAM user, letting your agent start its work from a known state.

Q: How do I handle pending uploads with Wasabi and LangChain?

You can call listpendingmultipartuploads. This shows you any incomplete data transfers that are sitting in the bucket. It's crucial for your agent to check this list before assuming a file upload finished.

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Connect Wasabi MCP to LangChain

Create your Vinkius account to connect Wasabi 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 Wasabi with LangChain

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Claude

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Manage Storage Infrastructure

You can build an agent that checks your cloud setup before making changes. First, the chain runs `list_storage_buckets` to see what buckets exist. Then, it might call `get_bucket_datacenter_location` to confirm where the data physically lives. This process allows the next step in the chain to decide if a new bucket is needed or if the existing one needs configuration changes.

Handle Object Lifecycle

Need an agent to clean up old files? The flow works this way: it calls `list_bucket_objects` to get file keys and sizes. Once the chain identifies stale data, it executes `delete_bucket_object`. This action is irreversible, so the agent needs solid confirmation before proceeding. This capability lets you build reliable cleanup routines that follow a clear sequence of checks and actions.

Configure Version Control

The chain can manage object history across multiple steps. It first calls `get_bucket_versioning_status` to check the current state. If versioning isn't active, it runs `enable_bucket_versioning`. This setup ensures that every change is recorded for later recovery. This gives you a powerful multi-step workflow where one step confirms policy and the next executes the necessary infrastructure change.

Setup guide

Set up Wasabi 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 Wasabi 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({
    "wasabi-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 Wasabi transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Wasabi MCP in LangChain

You use `get_bucket_datacenter_location` to get the physical region. This single tool call returns the precise geographic area where the data is housed, letting your agent ground its decisions in concrete facts.

Yep. You run `get_object_access_control` to pull the specific ACL for any file you care about. This gives your agent visibility into who has permission to read or write that data.

This MCP Server touches metadata regarding storage objects, specifically including file keys, sizes, and last modified dates. Your agent uses this data to make decisions about object retention.

Just call `list_storage_buckets`. This tool immediately returns a comprehensive list of every bucket visible to the authenticated IAM user, letting your agent start its work from a known state.

You can call `list_pending_multipart_uploads`. This shows you any incomplete data transfers that are sitting in the bucket. It's crucial for your agent to check this list before assuming a file upload finished.

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