Engram Rs

Created By
kael-bit3 months ago
Hierarchical memory for AI agents. Three-layer (buffer/working/core) with automatic decay, promotion, and semantic search.
Overview

Engram gives AI agents persistent, human-like memory. Memories flow through three cognitive layers — buffer (short-term), working (active knowledge), and core (long-term) — with automatic decay, promotion, and consolidation.

Features:

  • Semantic search via HNSW vector index
  • Automatic deduplication and merging
  • Namespace isolation for multi-agent setups
  • Session context extraction from LLM conversations
  • MCP protocol support (stdio transport)
  • Local-first, single-binary Rust server + SQLite

Works with Claude Desktop, Cursor, Windsurf, and any MCP-compatible client.

Server Config

{
  "mcpServers": {
    "engram": {
      "command": "npx",
      "args": [
        "-y",
        "engram-rs-mcp"
      ],
      "env": {
        "ENGRAM_URL": "http://localhost:3917",
        "ENGRAM_API_KEY": "",
        "ENGRAM_NAMESPACE": ""
      }
    }
  }
}
Project Info
Created At
3 months ago
Updated At
3 months ago
Author Name
kael-bit
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