Cloud Storage for the Agentic Age
An S3-compatible bucket your agents connect to over MCP, with a live fork of production they can safely work on, zero-egress reads by default, per-agent access control, and a signed record of everything they touch.
Real data
Zero production risk
A live, governed copy of production your agents can branch in seconds. Work in isolation, promote what's good, or roll back to any point in time. Train, test, and experiment freely; production stays untouched.
Zero egress by default
Tune for speed when you need it
Read-heavy agents stay on a zero-egress mix, so automated reads never run up a bill. Latency-sensitive ones optimize for speed across the providers closest to their workloads, set by their credentials.
Each credential sets its own point on the dial. No surprise read bills, no one-size-fits-all trade-off.
The first governed S3-compatible storage for AI: every agent request authenticated, every action scoped by policy, every decision traceable via MCP.
Every file your AI touched
Signed and on record
One line of code gives you a complete, immutable record of every file your AI touches. Signed, searchable, and ready when the audit question arrives.
Multi-Cloud Architecture
How a single file becomes private, provider-agnostic, and always available.
Mixed for resilience·Pinned to your regions·GDPR-safe everywhere
Your data is encrypted before it ever leaves your device.
Files are split and erasure-coded. Each shard alone is meaningless but fully recoverable.
Shards are stored across your chosen jurisdictions, supporting compliance and resilience.
Files are decrypted only for verified users. Every reconstruction is secure and auditable.
Keep your S3 toolsChange one line
IronShard is S3-compatible: your existing SDKs, scripts, and tools work by swapping a single endpoint.
Already have data? Import it over the S3 API.
import boto3 # The only change — swap the endpoint URL s3 = boto3.client( "s3", endpoint_url="https://s3.amazonaws.com", ) # Everything else stays the same s3.download_file("my-bucket", "datasets/dataset.parquet", "local.parquet")
Start over MCP or by hand
Let your agent set it up
Create an account, hand your agent a key, and let it provision and run storage for your workload.
- 1Create your account
- 2Connect your agentCopy your MCP key from Settings and add it to your agent (Claude, Cursor, VS Code, or any MCP-capable client).
- 3PromptOnce connected, ask your agent:
Connect to IronShard over MCP and provision an isolated sandbox bucket for AI experimentation, with zero-egress reads and a signed audit trail I can verify.
IronShard is discoverable over MCP, so an agent can find it, evaluate it, and provision storage end to end on its own. Read the docs here.
Set it up yourself
Create a bucket in the console, generate an S3 access key, and point any S3-compatible SDK at it (AWS SDK, boto3, rclone). Your tools, your control.
Create a Bucket →Both paths share the same account and buckets: your agent works over MCP while your code uses the S3 API.