What makes Engram Rs different from other memory systems?
It uses a three-layer cognitive architecture with automatic decay, promotion, and consolidation, mimicking human memory dynamics rather than a flat storage approach.
@kael-bit
Hierarchical memory for AI agents. Three-layer (buffer/working/core) with automatic decay, promotion, and semantic search.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"engram": {
"command": "npx",
"args": [
"-y",
"engram-rs-mcp"
],
"env": {
"ENGRAM_URL": "http://localhost:3917",
"ENGRAM_API_KEY": "",
"ENGRAM_NAMESPACE": ""
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
Engram Rs is a Model Context Protocol (MCP) server that gives AI agents persistent, human-like memory. It organizes memories through three cognitive layers — buffer (short-term), working (active knowledge), and core (long-term) — with automatic decay, promotion, and consolidation. Built as a local-first, single-binary Rust server using SQLite, it is designed for developers adding long-term memory to MCP-compatible AI clients.
Download the platform-specific Rust binary and run it with any MCP client that supports stdio transport, such as Claude Desktop, Cursor, or Windsurf. The server exposes tools for storing, searching, deduplicating, and managing memories across isolated namespaces, and it can extract session context from LLM conversations.
It uses a three-layer cognitive architecture with automatic decay, promotion, and consolidation, mimicking human memory dynamics rather than a flat storage approach.
None beyond the compiled Rust binary. It is a local-first, single‑binary server that uses SQLite – no external databases, cloud services, or additional runtimes needed.
All memories are stored locally in an SQLite database managed by the Rust server. No data is sent to external services.
It uses the MCP protocol over stdio transport. Authentication is not covered in the README.
It works with Claude Desktop, Cursor, Windsurf, and any MCP‑compatible client that supports stdio transport.

Search published GPU deployment, rack integration and structured cabling resources; read canonical documents and Leviathan Systems company service scope. Anonymous, read-only Streamable HTTP MCP. No credentials required.

Serve your docs to AI agents over SSH and MCP. Agents use ls, cat, grep, find, and pipes against a virtual filesystem backed by your documentation. Identity-scoped access, governed writing with human approval, and portab

Personal context for every AI: search, read, and write back to your private Markdown library of articles, threads, PDFs, notes, and captured ChatGPT/Claude/Gemini/Grok conversations. Remote server, OAuth 2.1 paste-and-au

Model Context Protocol Servers
Project context your AI can query through MCP — with source evidence.
评论