Step-by-step onboarding guide for connecting a new AI agent to Akasha. Use when setting up a new agent, configuring authentication, choosing a namespace strategy, or writing the initial system prompt for Akasha integration. Covers Python SDK, Node.js SDK, and raw HTTP/gRPC.
Monitor and manage an Akasha cluster — check node health, license status, cluster topology, and admin operations. Use when the agent needs to verify system health, inspect cluster state, manage users and API keys, or troubleshoot connectivity between nodes.
Store, retrieve, and query shared memory records in Akasha — a distributed cognitive fabric for intelligent agent collaboration. Use when the agent needs persistent memory, wants to share findings with other agents, or needs to read context written by other agents. Supports working, episodic, semantic, and procedural memory layers with automatic consolidation via the Nidra engine.
Monitor and interact with Akasha's Nidra consolidation engine — the subsystem that automatically consolidates episodic memories into semantic knowledge. Use when you need to check consolidation status, understand memory lifecycle, or query memory layer statistics.
Coordinate with other agents through pheromone-based stigmergy signals in Akasha. Use when you need to signal discoveries, request help, warn about issues, or coordinate work without direct agent-to-agent messaging. Pheromones decay over time (configurable half-life), creating natural priority based on recency and intensity.