> For the complete documentation index, see [llms.txt](https://vayl.gitbook.io/vayl-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://vayl.gitbook.io/vayl-docs/changelog/2026/v0.1.0-initial-release.md).

# v0.1.0 — Initial release

*July 2026*

The first public release of Vayl — reconciling memory for AI agents, over the Model Context Protocol.

## Highlights

* **Reconciling engine.** Supersede, retract, flag, coexist, and dedup, with a same-slot invariant (one active value per subject/scope). Events vs. state handling. Full history kept off the hot path.
* **MCP server.** 30+ tools across memory, safety, accountability, compliance, and administration. `vayl-mcp` (local stdio) and `vayl-server` (authenticated team HTTP).
* **Memory spaces.** Per-`(user_id, agent_id, run_id)` isolation for multi-user, multi-agent deployments.
* **Security by default.** At-rest encryption (Fernet with Argon2id key derivation), an Ed25519-signed, tamper-evident audit chain, and optional HashiCorp Vault key custody.
* **Access control.** API-key principals with role-based capabilities, tenant scoping, and optional OIDC SSO.
* **GDPR building blocks.** Erasure with signed receipts, DSAR export, and retention with a signed audit anchor.
* **Storage.** SQLite by default; optional Postgres for multi-writer scale with cross-process locking.
* **Retrieval.** Hybrid semantic + lexical ranking with bounded top-k, plus an optional Neo4j graph projection for relational queries.

## Requirements

Python 3.10+ (validated on free-threaded 3.14t). Any OpenAI-compatible LLM and embedder; defaults to a local Ollama endpoint with no egress.

Apache-2.0 · [github.com/vayl-dev/vayl](https://github.com/vayl-dev/vayl)


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