Can my AI agent debug broken uploads in Backblaze B2?

Yes. Ask your agent to list unfinished large files. It detects multipart upload shards that disconnected before completion, which consume billing quota. It provides granular visibility so you can safely clear dead streams via API.

Can the agent make my private bucket publicly accessible to serve CDN assets?

Yes. If commanded, the agent can update the bucket privacy setting from 'allPrivate' to 'allPublic'. This instantly routes objects to be fetched securely using friendly URLs for front-end hosting or CDN origins.

How does the agent handle file deletion safely using B2 protocol?

The agent can perform both soft deletes (hide file marker, triggering lifecycle purge later) or absolute hard version deletes. If you tell the agent to 'hide the file', the file remains physically safe but vanishes from directory listings.

Backblaze B2 MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Backblaze B2
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Backblaze B2 through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "backblaze-b2": {
            "transport": "streamable_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,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Backblaze B2, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Backblaze B2 MCP Server

Connect your Backblaze B2 account to any AI agent and manage your cloud storage architecture directly through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Backblaze B2 through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

O que você pode fazer

Buckets — Create, delete, update privacy (allPrivate/allPublic), and list globally mapped storage buckets
File Management — Hide files (soft delete), remove explicit file versions (hard delete), and list surface names
Health Validation — List unfinished large file chunks to find failed multipart uploads
File Intelligence — Retrieve granular file details, sizes, hashes (SHA1), and content types natively

Como funciona

1. Subscribe to this server
2. Enter your Backblaze B2 Application Key ID and Key
3. Start architecting storage and debugging files from Claude, Cursor, or any MCP-compatible client

Your AI agent now has the power to orchestrate secure and cost-effective object storage without leaving your editor.

Para quem é?

DevOps Engineers — rapidly verify bucket states, clean up abandoned file versions, and debug failed multipart streams
Backend Developers — create public and private storage domains directly from development spaces
System Administrators — audit object footprint securely and perform granular file integrity checks

The Backblaze B2 MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Backblaze B2 to LangChain via MCP

Follow these steps to integrate the Backblaze B2 MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Backblaze B2 via MCP

Why Use LangChain with the Backblaze B2 MCP Server

LangChain provides unique advantages when paired with Backblaze B2 through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Backblaze B2 MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Backblaze B2 queries for multi-turn workflows

Backblaze B2 + LangChain Use Cases

Practical scenarios where LangChain combined with the Backblaze B2 MCP Server delivers measurable value.

RAG with live data: combine Backblaze B2 tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Backblaze B2, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Backblaze B2 tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Backblaze B2 tool call, measure latency, and optimize your agent's performance

Backblaze B2 MCP Tools for LangChain (10)

These 10 tools become available when you connect Backblaze B2 to LangChain via MCP:

authorize_account

Uncovers the dynamically assigned apiUrl (e.g. api003.backblazeb2.com) natively orchestrating regional data ingress specifically assigned to your billing account. Verify and extract Backblaze global session routing endpoints

create_bucket

Bootstraps essential structures before assigning automated backup syncs overriding file lock retention bounds. Provision a fresh logical Storage Bucket partition

delete_bucket

Fails intentionally via 400 Bad Request if standard files or hidden object versions persist nested inside. Ensure all lifecycle rules completed purging prior to command. Irreversibly delete an entirely empty Backblaze Storage Bucket

delete_file_version

Instantly removes the storage footprint avoiding long-term retention hoarding. Irreversibly vaporize specific absolute chunk data from disk arrays

get_file_info

Obtain granular checksum and headers associated with one precise B2 File

hide_file

Does not actually delete binary payload, merely injects a null-marker shadowing the actual file ensuring b2_list_file_names ignores it, enforcing safe soft deletion logic. Mark an active B2 file as hidden leaving data for lifecycle sweep

list_buckets

Crucial to resolve immutable String Bucket IDs prerequisite to executing downstream CRUD operations strictly inside native borders. Retrieve the exact Storage Buckets existing globally on the B2 Account

list_file_names

Examines precise .pdf, .mp4 file locations avoiding hidden shadowed states produced by lifecycle overwrite semantics. Paginate primary surface-level object metadata from a specific Bucket

list_unfinished_large_files

Crucial for verifying broken API pipelines originating from external S3 clients failing CompleteMultipartUpload. Scan B2 nodes for stalled Multipart Upload chunk aggregates

update_bucket

Use only for static asset endpoints. Mutate global ACL privacy settings for a bounded Bucket

Example Prompts for Backblaze B2 in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Backblaze B2 immediately.

"What buckets do we have enabled in Backblaze B2 right now?"

"Create a new private bucket named 'ai-crawler-logs-2026' and make it private."

"Get the file details and SHA1 for the object 'index.html' in the public bucket."

Troubleshooting Backblaze B2 MCP Server with LangChain

Common issues when connecting Backblaze B2 to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Backblaze B2 + LangChain FAQ

Common questions about integrating Backblaze B2 MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.