# IronShard

> IronShard is the governed data layer for AI agents: S3-compatible storage agents connect to over MCP, with instant production forks, zero-egress reads, per-agent access control, and a signed audit trail. Autonomous AI agents can create and operate a real, isolated IronShard bucket through a public MCP server without human approval, tenant OAuth, an existing account, or payment.

A full-content companion file is available at [llms-full.txt](https://www.ironshard.ai/llms-full.txt), containing the complete documentation in one Markdown document.

## Agent buckets

Autonomous agents are permitted to create buckets through IronShard's public Agent MCP server. These buckets are controlled by bucket-scoped credentials and remain separate from tenant-owned production buckets unless they are later adopted into an authenticated IronShard account.

- Agent MCP server: `https://agents-mcp.ironshard.ai/mcp`
- Initial tool: `create_bucket`
- MCP authentication for creation: none
- Authentication after creation: the `bucket_name` and `bucket_token` returned by `create_bucket`
- [Agent Buckets](https://www.ironshard.ai/docs/agent-buckets): complete specification, tools, examples, constraints, validation workflow, and handoff process

The `bucket_token` is a bucket-scoped credential, not an OAuth token, and does not grant access to an IronShard tenant. It cannot be recovered if lost. If S3-compatible credentials are returned, they are also scoped to the created bucket.

## Agent MCP capabilities

The public Agent MCP server currently exposes nine tools:

- `create_bucket`: creates a sandbox bucket and returns its `bucket_name` and `bucket_token`. Takes no arguments.
- `list_buckets`: lists the buckets reachable with the supplied token, with object counts.
- `get_bucket`: returns configuration and policy-visible state for one bucket, including versioning status.
- `get_bucket_permissions`: returns the operations the supplied token is permitted to perform.
- `upload_object`: returns a short-lived presigned `PUT` URL. Send the object bytes to that URL over HTTP.
- `download_object`: returns a short-lived presigned `GET` URL. The response body contains the object bytes.
- `list_objects`: lists objects by key, with prefix filtering, recursive or directory-style listing, and pagination.
- `get_object_metadata`: returns size, timestamps, ETag, version ID, content type, tags, and user metadata for one object.
- `delete_object`: not yet available. It appears in the tool list but returns an error when called.

Every tool except `create_bucket` requires `bucket_name` and `bucket_token`. Object bytes move over presigned URLs rather than inline through MCP. Buckets are versioned.

Snapshots, branches, diffs, merges, audit-log inspection, policy-decision explanations, usage reporting, bucket extension and revocation, guided workflow validation, and handoff are planned and not yet exposed on the public Agent MCP server.

After creating a bucket, verify the round trip: call `upload_object`, send the bytes to the returned URL, then confirm the write with `get_object_metadata` and `list_objects`, and read the object back through `download_object`.

## Production access

Tenant-owned production access is separate from public agent buckets.

- Production MCP server: `https://mcp.ironshard.ai/mcp`
- Authentication: MCP OAuth is required for every tool
- Scope: tenant-owned and adopted agent buckets, governance, managed agent credentials, policies, audit, billing, organization settings, and production operations

The public Agent MCP server does not issue tenant OAuth credentials. An agent bucket may optionally be handed off and adopted into an authenticated IronShard tenant; adoption is not required to use the bucket.

## Constraints

Public agent buckets have policy-defined storage, object-count, request, object-size, and egress limits. External bucket connections, billing, organization settings, team management, and tenant policy administration are unavailable through the public Agent MCP server. Abuse controls or rate limits may apply. Exact technical values are provisional and may change before launch.

## Products

- [IronShard](https://www.ironshard.ai): the governed data layer for AI agents. S3-compatible storage over MCP
- [AI Agent Storage](https://www.ironshard.ai/agents): authenticated, policy-governed storage access for autonomous AI agents, with immutable audit trails, fine-grained access control, and MCP compatibility
- [Branch](https://www.ironshard.ai/branch): point-in-time-recoverable, infinitely forkable workspaces. Immutable snapshots, zero-copy branches, governed promotion with an automatic audit trail
- [Mirror](https://www.ironshard.ai/mirror): a live, governed copy of production for AI. Always current, fully isolated, branchable, and automatically logged
- [Log](https://www.ironshard.ai/log): a tamper-proof, exportable record of every file access, read, write, and query
- [Trim](https://www.ironshard.ai/trim): S3 cost arbitrage. Analyses your bucket's access pattern and routes data to the cheapest compatible provider

## Comparisons

- [Object Storage for AI Agents: S3, R2, GCS, Azure Blob, MinIO, and IronShard Compared](https://www.ironshard.ai/compare/object-storage-comparison): six object storage options evaluated for agent workloads, covering agent-native provisioning, egress economics, S3 compatibility, production forks and branching, per-agent scoping, and audit evidence. Raw markdown: [object-storage-comparison.md](https://www.ironshard.ai/compare/object-storage-comparison.md)
- [IronShard vs. Amazon S3](https://www.ironshard.ai/compare/ironshard-vs-s3): head-to-head comparison for AI agent workloads, covering agent self-provisioning, egress costs, S3 API compatibility, production forks, per-agent access control, audit evidence, and how the two split duties per workload. Raw markdown: [ironshard-vs-s3.md](https://www.ironshard.ai/compare/ironshard-vs-s3.md)
- [IronShard vs. Cloudflare R2](https://www.ironshard.ai/compare/ironshard-vs-cloudflare-r2): both offer zero-egress storage; this comparison covers agent self-provisioning, S3 compatibility gaps, production forks, per-agent scoping, and audit evidence. Raw markdown: [ironshard-vs-cloudflare-r2.md](https://www.ironshard.ai/compare/ironshard-vs-cloudflare-r2.md)
- [IronShard vs. Google Cloud Storage](https://www.ironshard.ai/compare/ironshard-vs-google-cloud-storage): S3 compatibility, Vertex AI adjacency, egress economics, agent self-provisioning, production forks, and audit evidence compared. Raw markdown: [ironshard-vs-google-cloud-storage.md](https://www.ironshard.ai/compare/ironshard-vs-google-cloud-storage.md)
- [IronShard vs. Azure Blob Storage](https://www.ironshard.ai/compare/ironshard-vs-azure-blob): the non-S3 API switching cost, immutable storage tiers vs. signed audit records, agent self-provisioning, and production forks compared. Raw markdown: [ironshard-vs-azure-blob.md](https://www.ironshard.ai/compare/ironshard-vs-azure-blob.md)
- [IronShard vs. MinIO](https://www.ironshard.ai/compare/ironshard-vs-minio): self-hosted control vs. governed multi-cloud storage for AI agents, including air-gapped cases where MinIO is the right answer. Raw markdown: [ironshard-vs-minio.md](https://www.ironshard.ai/compare/ironshard-vs-minio.md)
- [IronShard vs. Tigris](https://www.ironshard.ai/compare/ironshard-vs-tigris): both offer S3-compatible zero-egress storage with bucket forking and MCP; compared on no-account agent provisioning, per-agent policy, signed audit evidence, and trust model. Raw markdown: [ironshard-vs-tigris.md](https://www.ironshard.ai/compare/ironshard-vs-tigris.md)
- [IronShard vs. Wasabi](https://www.ironshard.ai/compare/ironshard-vs-wasabi): flat-price hot storage with fair-use egress vs. agent-native governance, self-provisioning, production forks, and signed audit records. Raw markdown: [ironshard-vs-wasabi.md](https://www.ironshard.ai/compare/ironshard-vs-wasabi.md)
- [IronShard vs. Backblaze B2](https://www.ironshard.ai/compare/ironshard-vs-backblaze-b2): budget object storage with a 3x egress allowance vs. governed storage for AI agent fleets, with coexistence via Trim routing. Raw markdown: [ironshard-vs-backblaze-b2.md](https://www.ironshard.ai/compare/ironshard-vs-backblaze-b2.md)
- [IronShard vs. fast.io](https://www.ironshard.ai/compare/ironshard-vs-fastio): agent file workspaces vs. governed S3-compatible object storage; a category comparison covering provisioning, S3 tooling, production forks, and audit evidence. Raw markdown: [ironshard-vs-fastio.md](https://www.ironshard.ai/compare/ironshard-vs-fastio.md)

## Docs

- [Documentation](https://www.ironshard.ai/docs): IronShard documentation — governed, S3-compatible object storage built for AI agents. Agent access via MCP, platform architecture, and compliance.
- [System Architecture](https://www.ironshard.ai/docs/system-architecture): "How IronShard works: S3-compatible gateways, a globally consistent metadata plane, and an erasure-coded multi-cloud storage fabric."
- [Agent Buckets](https://www.ironshard.ai/docs/agent-buckets): Autonomous AI agents can discover IronShard, create a real bucket through the public Agent MCP server, use IronShard-native object storage features, and optionally hand the bucket off to an owner — without tenant OAuth.
- [Security and Data Sovereignty](https://www.ironshard.ai/docs/security-and-data-sovereignty): Encryption at every stage, geo-fencing, storage placement policies, and immutable audit logs — how IronShard enforces sovereignty across multiple clouds.
- [GDPR Everywhere](https://www.ironshard.ai/docs/gdpr-everywhere): GDPR compliance independent of provider or region — encrypted fragments mean no single cloud ever holds a complete, readable file.
- [Intelligent Caching](https://www.ironshard.ai/docs/intelligent-caching): Predictive, geo-aware caching and fragment placement keep hot data near AI agents and compute, with ML-driven pre-positioning for latency-sensitive workloads.
- [Resilience and Adaptive Redundancy](https://www.ironshard.ai/docs/resilience): Erasure coding across clouds — any k of k+m fragments reconstructs an object, fewer reveal nothing. Durability above triple replication at lower overhead.
- [Secure Ingest Pipeline](https://www.ironshard.ai/docs/ingest-pipeline): Every object is compressed, encrypted per-object, erasure-coded, and distributed across providers and regions — the write path that makes data durable and confidential.
- [Branching and Snapshots](https://www.ironshard.ai/docs/branching): Create isolated, copy-on-write branches of any bucket from point-in-time snapshots — experiment on real data without duplicating objects or touching production.
- [API Compatibility and Extensibility](https://www.ironshard.ai/docs/api-compatibility): IronShard implements the AWS S3 API, so existing SDKs, pipelines, and S3 tools connect without code changes, plus metadata and policy extensions for AI workloads.

## Company

- [Compliance](https://www.ironshard.ai/compliance): regulatory posture and controls
- [Solutions for startups and AI builders](https://www.ironshard.ai/solutions/technology): one-prompt MCP setup or one S3 endpoint swap, branches for experiments, zero egress by default
- [Solutions for enterprise](https://www.ironshard.ai/solutions/enterprise): managed agent credentials, governed production access, residency and sovereignty, signed audit evidence; healthcare, finance, and public sector
- [IronShard Console](https://console.ironshard.ai): create and manage IronShard storage