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v0.0.1

moorcheh-ai/memantov0.0.1Apr 22, 2026by Neelpatel1604

AI Summary

Memanto v0.0.1 is the initial release of a production-ready semantic long-term memory system for AI agents, built on Moorcheh.ai's no-indexing database. It offers high-accuracy retrieval, zero-cost ingestion latency, and a comprehensive CLI and REST API ecosystem. The release includes robust developer integrations and a secure reference stack called MemantoClaw.

Key Highlights

  • High-accuracy retrieval (89.8% on LongMemEval) with zero-cost ingestion latency.
  • Zero-indexing semantic search enabling instant write-to-retrieval.
  • Comprehensive CLI and v2 REST API for programmatic memory management.
  • Native integrations with 13+ AI coding assistants and IDEs.
  • MemantoClaw reference stack combining OpenClaw and NVIDIA OpenShell.

New Features

  • Persistent identity with isolated memory namespaces for agents.
  • 6-hour active session windows with persistent memory access.
  • Support for 13 structured memory types (fact, preference, decision, etc.) with confidence scoring.
  • Zero-indexing semantic search for natural-language recall.
  • Complete memanto CLI with organized command groups (agent, memory, session, schedule, config, connect).
  • v2 REST API with dual authentication (Bearer API key and JWT session tokens).
  • Python httpx examples for both API key and session token flows.
  • Native integrations with 13+ AI coding assistants (Claude Code, Cursor, GitHub Copilot, etc.).
  • MemantoClaw reference stack for secure, sandboxed autonomous agents.

Full Release Notes

# Release Notes for v0.0.1

This is the **initial release** of **Memanto** - a production-ready semantic long-term memory system for AI agents. Built on Moorcheh.ai’s no-indexing semantic database, Memanto delivers zero-cost ingestion latency, state-of-the-art accuracy (89.8% on LongMemEval, 87.1% on LoCoMo), instant write-to-retrieval, and true semantic search across conversations, sessions, and workflows.

## Improvements

### Semantic Memory Engine
- **Agents**: Persistent identity with isolated memory namespaces (e.g. `customer-support-bot` or `dev-assistant`).
- **Sessions**: 6-hour active windows; memories persist forever and remain accessible across all future sessions.
- **Memories**: Semantic units supporting 13 structured memory types (`fact`, `preference`, `decision`, `goal`, `instruction`, `event`, etc.) with confidence scoring.
- **Zero-Indexing Semantic Search**: Memories are immediately available for natural-language recall with no indexing delay or background processing.
- **High-Accuracy Retrieval**: Matches intent and context (e.g., “User prefers email communication” → “How should we contact the user?”).

### Memanto CLI
- Complete `memanto` command-line interface installed via `pip install memanto`.
- Organized command groups: `agent` (create/activate/deactivate), `memory` (remember/recall/export), `session`, `schedule`, `config`, `connect` (integrations), and core utilities.
- Global options: `--help`, `--version`.
- Quickstart workflow:
  ```bash
  memanto                  # initial API key configuration
  memanto agent create my-agent
  memanto agent activate my-agent
  memanto remember "Project kickoff is Monday" --type event
  memanto recall "When is project kickoff?"
  ```
### REST API & Authentication

- Full **v2 HTTP API** for programmatic memory management, agent lifecycle, recall, and generative answers.
- Get your Moorcheh API key from [console](https://console.moorcheh.ai/api-keys)
- Secure **dual authentication**:
  - `Authorization: Bearer <moorcheh-api-key>` for all requests.
  - `X-Session-Token: <jwt>` (6-hour session token obtained via `/agents/{agent_id}/activate`) for memory operations.
- JWT token introspection support and session extension endpoint included.
- Python `httpx` examples provided for both API key and session token flows.

### Developer Integrations

- Native integrations with **13+ AI coding assistants and IDEs**:
  - Claude Code, Cursor, Cline, Windsurf, Continue, GitHub Copilot, OpenCode, Goose, Roo, Antigravity, Augment, Gemini CLI, Codex.
- Simple connection via `memanto connect <tool>` (project-local or `--global` scope).
- Enables persistent context storage (preferences, decisions, architecture choices) and cross-session recall inside coding tools.
- Supports multi-tool and multi-environment setups (separate agents per tool or environment).

### MemantoClaw

- Open-source reference stack for secure, always-on memory-augmented agents.
- Combines **OpenClaw** (autonomous agent framework), **NVIDIA OpenShell** (hardened sandbox with seccomp, Landlock, filesystem restrictions), and Memanto/Moorcheh memory.
- One-command provisioning: `memantoclaw onboard` (automatically configures inference routing, credentials, and zero-config Memanto memory bridge).
- Enhanced security: stricter policies than community OpenShell, credential filtering, immutable gateway config, and host-bridge memory architecture.

### Getting Started

See the official quickstart in the [Introduction](https://docs.memanto.ai/getting-started/introduction) and [CLI Overview](https://docs.memanto.ai/cli/overview).  
Deployment options include Docker, Python, AWS ECS, Google Cloud Run, Azure Container Instances, or local single-machine setups.

### Documentation

- Full documentation: https://docs.memanto.ai
- CLI command reference, API authentication guide, integration setup, and MemantoClaw overview are all live.
- Moorcheh.ai base documentation: https://docs.moorcheh.ai

This **v0.0.1** release establishes the complete Memanto ecosystem for production-grade long-term memory in AI agents and developer workflows.