Crosmos
@crosmos-labs
Persistent memory for AI agents. Give your coding assistant organizational context that compounds — search memories with hybrid retrieval, store anything with auto entity extraction, and query a living knowledge graph that gets smarter over time.
Overview
What is Crosmos?
Crosmos is a persistent memory layer for AI agents. It enables agents to store and retrieve organizational knowledge across sessions using a temporal knowledge graph with hybrid retrieval.
How to use Crosmos?
Install via npx @crosmos/crosmos-mcp setup which auto-detects MCP clients, or configure manually with a JSON block setting the CROSMOS_API_KEY (obtainable at console.crosmos.dev). Supported clients include Claude Desktop, Claude Code, Cursor, VS Code, Windsurf, opencode, Cline, Roo-Cline, and Zed.
Key features of Crosmos?
- Graph-native memory with entity and relationship linking
- Temporal – every fact is timestamped for time‑travel queries
- Hybrid retrieval (semantic, keyword, graph, temporal)
- Automatic entity and relationship extraction from raw text
- Multi‑space isolation for projects, teams, or agents
- Four retrieval signals fused into a single ranked result
Use cases of Crosmos?
- Store and retrieve organizational knowledge across AI agent sessions
- Query the knowledge graph as it existed at any past point in time
- Isolate memory by project, team, or agent using named spaces
- Allow agents to maintain persistent context without resets
- Enable hybrid search combining semantic meaning with graph traversal
FAQ from Crosmos
What is Crosmos and how does it differ from flat vector databases?
Crosmos uses a temporal knowledge graph that links memories as entities and relationships, not just flat vectors, enabling richer context and time
