Reverie 是 KnowAll AI 为 AI 代理开发的 Neo4j 知识图谱内存，通过 MCP 运行。它以 @knowall-ai/reverie] 的名称发布在 npm 上（遗留包 @knowall-ai/mcp-neo4j-agent-memory 的继任者）。GitHub 仓库现为 knowall-ai/mcp-reverie，旧的 URL 会重定向。

Reverie 将代理的记忆从一堆事实转化为其世界中实体及其关系的地图，并保持该地图的健康状态。它是 MCP 服务器，任何使用 Model Context 协议（Claude Desktop、OpenClaw、Azure AI Foundry、Cursor 等）的代理都会获得相同的图表;Hermes Agent 内存提供者的版本存在于 Hermes-reverie 中。

为什么是幻想

• 一个类型化实体图，不是事实存储。 人、组织、项目、地点、概念、会议和决策都是带有类型关系的节点。“我们和爱尔兰足球协会的谁谈过Winnie？”是图游走，不是相似性搜索。
• 当你说“Benjamin”时，搜索结果是“Ben”。 混合关键词+语义+模糊名称搜索，默认本地嵌入（无API密钥），OpenAI、Azure OpenAI、Ollama或Voyage只需一个配置切换即可访问。
• **它会做梦。

Reverie — graph memory that dreams

Reverie is KnowAll AI’s Neo4j knowledge-graph memory for AI agents, served over MCP. It is published on npm as @knowall-ai/reverie (successor to the legacy package @knowall-ai/mcp-neo4j-agent-memory). The GitHub repository is now knowall-ai/mcp-reverie, and old URLs redirect.

Reverie turns an agent’s memory from a pile of facts into a map of the entities in its world and how they relate, and keeps that map healthy. It is an MCP server, so any agent that speaks the Model Context Protocol (Claude Desktop, OpenClaw, Azure AI Foundry, Cursor…) gets the same graph; a Hermes Agent memory-provider flavour lives in hermes-reverie.

Why Reverie

• A typed entity graph, not a fact store. People, organisations, projects, places, concepts, meetings and decisions are nodes with typed relationships. “Who at the Irish FA have we talked to about Winnie?” is a graph walk, not a similarity search.
• Search that finds “Ben” when you say “Benjamin”. Hybrid keyword + semantic + fuzzy name search, with local embeddings by default (no API key) and OpenAI, Azure OpenAI, Ollama or Voyage a config switch away.
• It dreams. A dream tool merges duplicates safely, canonicalises labels, re-embeds, counts orphans and flags nodes that have become property dumps, so a nightly job can keep the graph clean.
• One graph, any agent. KnowAll runs Sallie (OpenClaw) and Poppie (Hermes) against the same conventions; Reverie is how they share what they know.
• LLM-driven, transparent tools. Simple atomic operations; the model does the entity recognition and conflict resolution, and every action is explicit.
• Yours to run. Neo4j on your own machine or VM. Nothing leaves it unless you choose a remote embedding provider.

Quick Start 🚀

You can run this MCP server directly using npx:

npx -y @knowall-ai/reverie

Or add it to your Claude Desktop configuration:

{
  "mcpServers": {
    "reverie": {
      "command": "npx",
      "args": ["-y", "@knowall-ai/reverie"],
      "env": {
        "NEO4J_URI": "bolt://localhost:7687",
        "NEO4J_USERNAME": "neo4j",
        "NEO4J_PASSWORD": "your-password",
        "NEO4J_DATABASE": "neo4j"
      }
    }
  }
}

Features

• 🧠 Persistent Memory Storage - Store and retrieve memories across conversations
• 🔗 Semantic Relationships - Create meaningful connections between memories (KNOWS, WORKS_AT, CREATED, etc.)
• 🔍 Hybrid Search - Keyword plus semantic search across all memory properties, with local embeddings by default