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MCP Server Rabel

@jaspertvdm

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

jaspertvdm

提交者

Jasper van de Meent

关于 MCP Server Rabel

Project description

#mcp-server#ai-memory#local-first

MCP Server Rabel 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "rabel": {
      "command": "python",
      "args": [
        "-m",
        "mcp_server_rabel"
      ],
      "env": {}
    }
  }
}

MCP Server Rabel 工具

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。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Mcp Server Rabel?

Mcp Server Rabel (Recidive Active Brain Environment Layer) is a local-first AI memory server that gives AI assistants persistent memory with semantic search, graph relations, and soft pipelines. Inspired by Mem0 and evolved for HumoticaOS, it runs 100% locally with no cloud, no API keys, and no data leaving the machine.

How to use Mcp Server Rabel?

Install via pip: pip install mcp-server-rabel (basic) or pip install mcp-server-rabel[full] (adds vector search and embeddings). Add to Claude CLI with claude mcp add rabel -- python -m mcp_server_rabel. Tools include rabel_add_memory, rabel_search, rabel_add_relation, rabel_get_guidance, and rabel_next_step.

Key features of Mcp Server Rabel

  • 100% local, zero cloud dependencies
  • Semantic memory storage and retrieval
  • Knowledge graph with entity relations
  • Soft pipelines for guided step-by-step tasks
  • Bilingual support (Dutch and English)
  • Graceful degradation: works without vector search
  • SQLite storage with optional sqlite-vec

Use cases of Mcp Server Rabel

  • Remember facts about users, team members, or projects
  • Semantically search past memories using natural language
  • Build and query a knowledge graph of entities and relationships
  • Guide AI assistants through multi-step processes with soft pipelines

常见问题

1

What dependencies does Mcp Server Rabel require?

With the basic install, only text storage and LIKE-based search are available. The `[full]` option adds vector search via sqlite-vec and embeddings via Ollama nomic-embed-text. Ollama must be running locally for semantic search.

2

Does Mcp Server Rabel work without internet?

Yes. It is designed to work entirely offline. No cloud services, tracking, or API keys are needed.

3

How does search work without vector embeddings?

Without the `[full]` extras, text search uses SQL `LIKE` queries. With embeddings, semantic (vector) search becomes available.

4

Can I add relations between memories?

Yes. The `rabel_add_relation` tool stores a subject–predicate–object triple, and `rabel_get_relations` retrieves them, enabling a knowledge graph.

5

What languages are supported for soft pipelines?

Soft pipeline guidance is available in both English and Dutch, more languages are planned.

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