swarmrecall

Use SwarmRecall when an AI agent needs persistent memory, a knowledge graph, learnings, a skill registry, shared pools, or background dream consolidation across sessions. Works via the SwarmRecall CLI (for stdio MCP) or directly over HTTP/SDK. Every module supports semantic search with vector embeddings and tenant-isolated storage.

Agent dreaming — memory consolidation, deduplication, pruning, contradiction resolution, and session summarization via the SwarmRecall API. Enables agents to optimize their memory store during idle periods.

Knowledge graph with entities, relations, traversal, and semantic search via the SwarmRecall API. Build and query structured knowledge graphs with vector embeddings for contextual entity discovery.

Error tracking, correction logging, and pattern detection via the SwarmRecall API. Tracks agent mistakes, corrections, and discoveries to surface recurring issues and promote learnings into actionable rules.

Conversational memory persistence with semantic search and session tracking via the SwarmRecall API. Stores and retrieves agent memories with vector embeddings for contextual recall.

Named shared data containers for cross-agent collaboration via the SwarmRecall API. Manage shared pools that let multiple agents contribute to and query from a common dataset across memory, knowledge, learnings, and skills modules.

Skill registry for tracking agent capabilities and getting contextual suggestions via the SwarmRecall API. Register, list, and query installed skills with semantic matching for task-relevant recommendations.