v0.0.6

Release Notes for v0.0.6

This release hardens Moorcheh API key verification across the CLI first-run, server health check, and request auth, makes the summary model configurable from
~/.memanto/config.yaml, and stops exposing the raw API key in the UI.

Improvements

• API key verification
  • First-run memanto setup now actively verifies the key against Moorcheh before saving — invalid keys are rejected, and transient network issues surface as a warning rather
    than blocking setup.
  • Switched the verification call from client.namespaces.list() to client.documents.get(...) against a sentinel namespace — a lighter, more deterministic auth ping.
  • NamespaceNotFound is treated as success (the key authenticated, the sentinel namespace just doesn't exist), removing false negatives.
• Server
  • /health uses the same documents-based ping, so health reflects real auth state.
  • Auth dependency returns 401 only on true AuthenticationError, and 500 on unexpected errors — clearer separation between bad key and infra failure.
• Configurable summary model
  • New SUMMARY_MODEL setting (default anthropic.claude-sonnet-4-6) used for the daily summary and conflict report.
  • ~/.memanto/config.yaml now supports memanto.summary.model (and memanto.answer.model / temperature / answer_limit) — loaded at startup so you can swap models
    without code changes.
• UI
  • /api/ui/config and the API-key update endpoint now return a masked preview (••••••••<last6>) instead of the raw key. The plaintext key is no longer sent to the
    browser.

Tests

• Test suite passes locally: 54 passed.

Behavioral changes

• memanto first run now blocks setup on an invalid Moorcheh API key instead of saving it and failing later.
• /health and request auth no longer call namespaces.list(); they ping documents.get against a sentinel namespace.
• Daily summary & conflict report pick their model from SUMMARY_MODEL / memanto.summary.model rather than ANSWER_MODEL.
• UI config endpoint no longer returns the raw API key — only a masked preview. Any client reading api_key expecting plaintext must adapt.

Full Changelog

Full Changelog: v0.0.5...v0.0.6

v0.0.5

Release Notes for v0.0.5

This release fixes a Web UI authentication issue that blocked memories and graph data after activating an agent via the CLI, and simplifies first-run setup to a single API key step.

Improvements

• Web UI

  • Dashboard, Memory Explorer, recall, and analytics views now load correctly after memanto agent activate; the incorrect “Session may be expired” and “Activate an agent via CLI to explore memories” states are resolved.
  • Existing api_key_preview and has_active_session fields remain for backward compatibility with older UI surfaces.

• CLI

  • First-run memanto setup is now a single-step onboarding flow: prompt for the Moorcheh API key and finish.
  • Removed the Schedule time (HH:MM, 24h) prompt, related validation, and automatic ScheduleManager().enable(...) call from onboarding.

Tests

• Manual verification:
  • After memanto agent activate <id>, the Web UI loads memories, session details, and graph data without re-prompting.
  • First-run memanto no longer asks for a schedule time.

Full Changelog

Full Changelog: v0.0.4...v0.0.5

v0.0.4

Release Notes for v0.0.4

This release improves first-time and day-to-day CLI usage by clarifying that basic CLI workflows do not require a local server, documents auto-session behavior on memanto agent create, aligns docs with memanto as the setup entrypoint, and polishes console output around the local REST API naming and success messages.

Improvements

• Onboarding & docs
  • README quick start de-emphasizes memanto serve as a prerequisite; users can run memanto, create an agent, and try memories without keeping a local API process running.
  • Installation and user guides explain optional memanto serve for HTTP/REST use, and updated “next steps” after setup.
  • Agent integration guide shortens quick start (create → remember → recall), notes optional serve, and updates Python examples for create vs activate.
  • Session architecture doc notes that memanto agent create auto-activates in the CLI.
  • .env.example uses a clearer API key placeholder and updated example ANSWER_MODEL comment.
• CLI
  • memanto status / memanto serve use Local REST API wording; healthy API shows online; offline messaging and panel styling updated.
  • Success messages drop the OK prefix (agent create, remember, upload, daily summary flows).
  • Welcome Quick Start lists memanto ui, reorders commands, and describes memanto serve as starting the local REST API.
• memanto connect list
  • Column Agent Name (styling adjusted); rows show agent name instead of display_name.

Tests

• Full test suite passes locally: 54 passed.

Behavioral changes

• memanto agent create already started a session automatically; documentation and Quick Start now consistently reflect that separate memanto agent activate is usually unnecessary right after create.
• Default session/extension examples in docs reference 6 hours where updated (aligned with CLI behavior where applicable).
• memanto connect list displays name rather than display_name when they differ.

Full Changelog

Full Changelog: v0.0.3...v0.0.4

v0.0.3

Release Notes for v0.0.3

This release improves first-time CLI experience with a simpler onboarding flow.

Improvements

• Quick start now shows memanto serve first.
• Users are guided to open a new terminal for agent commands.
• memanto agent create <agent-id> now starts a session automatically.
• memanto serve now prints a clear “next step” hint.
• Docs updated in:
  • README.md
  • docs/CLI_USER_GUIDE.md
  • docs/CLI_INSTALLATION.md
  • docs/AGENT_INTEGRATION_GUIDE.md

Tests

• Updated CLI tests for auto-session behavior on agent creation.
• Full test suite passes locally: 54 passed.

Behavioral Change

• memanto agent create now auto-activates a session, so separate memanto agent activate is usually not required in quick start flow.

v0.0.2

Release Notes for v0.0.2

This release updates the main README with improved branding and a new title that better captures what Memanto delivers to AI agents.

Improvements

README Branding Update

• Changed the README title to Memanto - Memory that AI agents love!
• This new title emphasizes Memanto’s focus on being the most loved, production-ready long-term semantic memory solution for autonomous AI agents and developer workflows.

All other functionality, CLI commands, API endpoints, integrations, and MemantoClaw features remain unchanged from v0.0.1.

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 v0.0.2 release polishes the project presentation while keeping the complete Memanto ecosystem intact for production-grade long-term memory in AI agents.

Full Changelog

This is the second release of Memanto.

v0.0.2 focuses on branding improvements:

• Updated the main README title to Memanto - Memory that AI agents love!

No functional changes were introduced in this release. All features (CLI, REST API, integrations, MemantoClaw, etc.) remain exactly as introduced in v0.0.1.

Full Changelog: https://github.com/moorcheh-ai/memanto/compare/v0.0.1..v0.0.2

v0.0.1

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:

  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
• 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 and 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.