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v0.6.0 — AI-Native Architecture

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@hvrcharon1 hvrcharon1 released this 01 Jul 17:50
v0.6.0
54f6b30

AI-Native Architecture for Autonomous Agents

AgentDB v0.6.0 introduces 5 new storage layers, an MCP server interface, and full multi-language binding coverage — making it a complete embedded database purpose-built for AI agents.

New Storage Layers

Layer Purpose
Tool Registry Register tools with JSON Schema parameters, log invocations with latency
Audit Log Immutable append-only provenance trail with actor/action/reason
Context Window Token-budgeted context management with priority and relevance scoring
Prompt Templates Versioned templates with {{placeholder}} rendering and model hints
Data Labels Privacy-by-design classification (PII, sensitive, internal, etc.)

MCP Server Interface

Full Model Context Protocol implementation:

  • JSON-RPC 2.0 transport
  • tools/list — 21 tools with JSON Schema input definitions
  • tools/call — invoke any AgentDB operation
  • resources/list / resources/read — database statistics

Multi-Language Bindings

All 5 new layers are exposed across:

  • Rust (core) — direct API
  • C FFI — 14 new functions in agentdb.h
  • Node.js (napi-rs) — TypeScript declarations included
  • Go (cgo) — idiomatic Go wrappers
  • Java (JNI) — AgentDB.java with full Javadoc
  • C# (P/Invoke) — AgentDB.cs with XML docs
  • WASM (wasm-bindgen) — browser-ready, JSON interchange
  • Async (Tokio) — AsyncToolStore, AsyncAuditStore, AsyncContextStore, AsyncPromptStore, AsyncLabelStore

Stats

  • 13 storage layers total
  • 231+ tests passing
  • Zero clippy warnings
  • Schema v5 with 6 new tables

Install

# Rust
cargo add datacules-agentdb

# Node.js
npm install @datacules/agentdb

# Python
pip install datacules-agentdb

Full Changelog: v0.5.3...v0.6.0

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