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 CrewAI 10 tools — connect in under 2 minutes

Name: Backblaze B2
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Backblaze B2 through Vinkius, pass the Edge URL in the `mcps` parameter and every Backblaze B2 tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Backblaze B2 Specialist",
    goal="Help users interact with Backblaze B2 effectively",
    backstory=(
        "You are an expert at leveraging Backblaze B2 tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Backblaze B2 "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About Backblaze B2 MCP Server

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

When paired with CrewAI, Backblaze B2 becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Backblaze B2 tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Backblaze B2

Why Use CrewAI with the Backblaze B2 MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Backblaze B2 through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Backblaze B2 + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Backblaze B2 for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Backblaze B2, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Backblaze B2 tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Backblaze B2 against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Backblaze B2 MCP Tools for CrewAI (10)

These 10 tools become available when you connect Backblaze B2 to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Backblaze B2 + CrewAI FAQ

Common questions about integrating Backblaze B2 MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.