Backblaze B2 MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Backblaze B2 through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Backblaze B2 "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Backblaze B2?"
)
print(result.data)
asyncio.run(main())
* 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.
Pydantic AI validates every Backblaze B2 tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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 Pydantic AI 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 Pydantic AI via MCP
Follow these steps to integrate the Backblaze B2 MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Backblaze B2 with type-safe schemas
Why Use Pydantic AI with the Backblaze B2 MCP Server
Pydantic AI provides unique advantages when paired with Backblaze B2 through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Backblaze B2 integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Backblaze B2 connection logic from agent behavior for testable, maintainable code
Backblaze B2 + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Backblaze B2 MCP Server delivers measurable value.
Type-safe data pipelines: query Backblaze B2 with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Backblaze B2 tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Backblaze B2 and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Backblaze B2 responses and write comprehensive agent tests
Backblaze B2 MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Backblaze B2 to Pydantic AI 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 Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting Backblaze B2 to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiBackblaze B2 + Pydantic AI FAQ
Common questions about integrating Backblaze B2 MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Backblaze B2 with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Backblaze B2 to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.