Enables Claude agents to checkpoint their context state and reset back to saved points with handoff messages, maintaining clean context windows during complex tasks by avoiding fragmented summaries from compactions.
Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.
Japan Operations OS for AI agents — 14 knowledge domains covering regulations, protocols, calendar, travel, food culture, language, disaster safety, daily life, and persistent memory. 31 MCP tools via REST + Streamable HTTP.
MCP server for the Trollspace API that exposes 47 type-safe tools for managing snippets, nuggets, todos, ideas, tools, repos, travel, subscriptions, and more.
Provides AI agents an auditable memory layer with provable deletion via signed certificates, a tamper-evident hash-chained audit trail, and bi-temporal time-travel recall over SQLite or Postgres.
An embedded knowledge graph in one SQLite file, exposing a MCP server for agents to read and write entities and relationships with full audit trail and time travel.
Provides Claude with a persistent local memory and structured knowledge graph to track project states, tasks, and historical decisions across different chat sessions. It enables users to recall information using keyword relevance, time-travel queries, and dependency analysis for complex project management.
Enables LLM agents to query a bi-temporal property graph using verified temporal operators via MCP, with auditable claims and correction-aware time travel.
Provides Claude with persistent local memory and a structured knowledge graph for tracking project states, task dependencies, and historical context. It enables users to store notes, manage task relationships, and perform time-travel queries to reconstruct past information without relying on cloud services.
Enables AI agents to store and recall durable facts, decisions, and lessons over MCP using hybrid semantic and keyword search, typed memories, graph relations, sessions, and time-travel queries. Runs locally with no server process or API key, persisting everything to files that both agents and a CLI can share.
Enables LLM assistants to store, retrieve, and update user-specific context memory including travel preferences and general information through a chat interface. Provides analytics on tool usage patterns and token costs for continuous improvement.
Enables analysis of documents far larger than an LLM's context window by letting the model issue constrained symbolic commands that execute server-side against in-memory handles, so only compact result stubs—rather than raw text—travel through the conversation. It also provides server-side memo storage with expandable handles, letting agents retain and retrieve large context across long sessions at a fraction of the token cost.
Gives AI agents persistent memory with bi-temporal tracking, automatically extracting entities from natural language and enabling time-travel queries to understand facts as they existed at any point in history.
Enables intelligent travel planning by combining weather forecasts and route calculations for destinations. Provides personalized travel recommendations based on weather conditions and supports trip planning with persistent conversation memory.
Enables AI agents to run an AI-driven text interactive fiction engine by initializing a worldview from a setting, resolving player actions through academic combat, trade, social and karma models, pulling narration context, advancing turns, and tracking emergent events across million-turn campaigns with tiered memory and summaries. Also imports SillyTavern character cards and world-info lorebooks, travel and codex tracking, snapshots, and serves a read-only live status panel.