openmemory-rag-mcp

openmemory-rag-mcp

MCP server for importing documents into OpenMemory RAG knowledge base. Supports file uploads, URL imports, text ingestion, and knowledge base search.

Category
访问服务器

README

OpenMemory RAG MCP Server

MCP server for importing documents into OpenMemory RAG knowledge base. Supports file uploads, URL imports, and text content ingestion.

Features

  • 📄 Import Files: PDF, DOCX, TXT, MD, HTML
  • 🌐 Import URLs: Webpages, articles, documentation
  • 📝 Import Text: Raw text content
  • 🔍 Search: Query the knowledge base

Installation

npm install
npm run build

Configuration

Set environment variables:

export OPENMEMORY_URL="http://localhost:8080"
export OPENMEMORY_USER_ID="rag_user"

Usage

With Claude Desktop

Add to ~/.config/claude/claude_desktop_config.json:

{
  "mcpServers": {
    "openmemory-rag": {
      "command": "node",
      "args": ["/path/to/openmemory-rag-mcp/dist/index.js"],
      "env": {
        "OPENMEMORY_URL": "http://localhost:8080",
        "OPENMEMORY_USER_ID": "my_knowledge_base"
      }
    }
  }
}

With Cursor

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "openmemory-rag": {
      "command": "node",
      "args": ["/path/to/openmemory-rag-mcp/dist/index.js"],
      "env": {
        "OPENMEMORY_URL": "http://localhost:8080"
      }
    }
  }
}

With Windsurf

Add to ~/.windsurf/mcp.json:

{
  "mcpServers": {
    "openmemory-rag": {
      "command": "node",
      "args": ["/path/to/openmemory-rag-mcp/dist/index.js"]
    }
  }
}

Available Tools

1. import_file

Import a local file into the knowledge base.

Example:

"Import the file /home/user/document.pdf into my knowledge base"

Parameters:

  • file_path (required): Absolute path to the file
  • user_id (optional): User ID for the knowledge base
  • tags (optional): Array of tags

2. import_url

Import content from a URL.

Example:

"Import this article: https://example.com/article"

Parameters:

  • url (required): URL to import
  • user_id (optional): User ID
  • tags (optional): Array of tags

3. import_text

Import raw text content.

Example:

"Save this to my knowledge base: [your text content]"

Parameters:

  • content (required): Text content
  • title (optional): Title for the content
  • user_id (optional): User ID
  • tags (optional): Array of tags

4. search_knowledge

Search the knowledge base.

Example:

"Search my knowledge base for information about Python"

Parameters:

  • query (required): Search query
  • user_id (optional): User ID to search within
  • limit (optional): Maximum results (default: 5)

Prerequisites

  • OpenMemory backend running on http://localhost:8080
  • Node.js 18+

Quick Start

  1. Start OpenMemory backend:
cd /path/to/OpenMemory/packages/openmemory-js
npm run dev
  1. Build MCP server:
cd openmemory-rag-mcp
npm install
npm run build
  1. Configure AI tool (see Usage section above)

  2. Restart AI tool (Claude/Cursor/Windsurf)

  3. Test:

"Import the file /home/user/notes.pdf"
"Search for Python programming"

Supported File Types

Type Extensions
Documents .pdf, .docx, .txt, .md, .html
Web Any URL
Text Raw text content

Example Workflow

User: "Import my research paper at /home/user/research.pdf"
AI: ✅ File imported successfully!
    Memory ID: abc-123
    Tokens: 5000
    Strategy: root-child
    Sections: 3

User: "What does my research paper say about machine learning?"
AI: 🔍 Found 2 results for "machine learning":
    1. [Score: 0.892] Machine learning is a subset of artificial intelligence...
    2. [Score: 0.845] The paper discusses various ML algorithms including...

Troubleshooting

MCP tools not showing up

  • Ensure OpenMemory backend is running: curl http://localhost:8080/health
  • Check MCP config file path is correct
  • Restart AI tool after configuration

Import fails

  • Verify file path is absolute
  • Check file permissions
  • Ensure OpenMemory backend is accessible

Search returns no results

  • Verify user_id matches the one used during import
  • Check if content was actually imported
  • Try broader search terms

Development

# Watch mode
npm run watch

# Build
npm run build

# Run directly
npm start

License

MIT

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选