memphora

@Memphora/memphora
Hosted
0 Stars 27 次浏览 Memphora 更新于 2026-08-23

Add persistent memory to AI assistants. Store and recall info across conversations.

MCP 服务配置

复制以下 JSON 到 OPClaw 或其他 MCP 客户端的配置文件中即可使用

{
  "mcpServers": {
    "memphora-mcp": {
      "args": [
        "memphora-mcp@0.1.3"
      ],
      "command": "uvx"
    }
  }
}

可用工具 (5 个)

该服务在 MCP 协议中暴露的工具,AI 可按需调用

tavily_search 14 个参数 需填 1 项

Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.

必填参数:query

tavily_extract 6 个参数 需填 1 项

Extract content from URLs. Returns raw page content in markdown or text format.

必填参数:urls

tavily_crawl 11 个参数 需填 1 项

Crawl a website starting from a URL. Extracts content from pages with configurable depth and breadth.

必填参数:url

tavily_map 8 个参数 需填 1 项

Map a website's structure. Returns a list of URLs found starting from the base URL.

必填参数:url

tavily_research 2 个参数 需填 1 项

Perform comprehensive research on a given topic or question. Use this tool when you need to gather information from multiple sources to answer a question or complete a task. Returns a detailed response based on the research findings.

必填参数:input

服务介绍

<!- - mcp-name: io.github.Memphora/memphora - ->

# What is this?

This MCP server connects your AI assistant to Memphora, giving it the ability to:

  • Remember information across conversations
  • Search your personal knowledge base
  • Extract insights from conversations automatically
  • Recall your preferences, facts, and context

# Quick Start

# # 1. Install

#  Using pip
pip install memphora-mcp

#  Or using uvx (recommended for Claude Desktop)
uvx memphora-mcp

# # 2. Get Your API Key

  1. Go to memphora.ai/dashboard
  2. Create an account or sign in
  3. Copy your API key from the dashboard

# # 3. Configure Claude Desktop

Add to your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "memphora": {
      "command": "uvx",
      "args": ["memphora-mcp"],
      "env": {
        "MEMPHORA_API_KEY": "your_api_key_here",
        "MEMPHORA_USER_ID": "your_unique_user_id"
      }
    }
  }
}

# # 4. Restart Claude Desktop

Close and reopen Claude Desktop. You should see the Memphora tools available!

# Usage Examples

# # Storing Memories

Just tell Claude something about yourself:

You: "I work at Google as a software engineer"
Claude: [stores memory] "Got it! I'll remember that you work at Google as a software engineer."

You: "My favorite programming language is Python"
Claude: [stores memory] "Noted! I'll remember that Python is your favorite programming language."

# # Recalling Memories

Ask Claude about things you've told it before:

You: "Where do I work?"
Claude: [searches memories] "You work at Google as a software engineer."

You: "What programming languages do I like?"
Claude: [searches memories] "Your favorite programming language is Python."

# # Automatic Context

Claude will automatically search your memories when relevant:

You: "Can you help me with some code?"
Claude: [searches memories for context]
        "Sure! Since you prefer Python and work at Google, I'll write this in Python 
         following Google's style guide..."

# Available Tools

| Tool | Description |
|- -- -- -|- -- -- -- -- -- --|
| memphora_search | Search memories for relevant information |
| memphora_store | Store new information for future recall |
| memphora_extract_conversation | Extract memories from a conversation |
| memphora_list_memories | List all stored memories |
| memphora_delete | Delete a specific memory |

# Configuration Options

| Environment Variable | Description | Default |
|- -- -- -- -- -- -- -- -- -- --|- -- -- -- -- -- --|- -- -- -- --|
| MEMPHORA_API_KEY | Your Memphora API key | Required |
| MEMPHORA_USER_ID | Unique identifier for your memories | mcp_default_user |

# Using with Other MCP Clients

# # Cursor

Add to your Cursor settings:

{
  "mcp": {
    "servers": {
      "memphora": {
        "command": "uvx",
        "args": ["memphora-mcp"],
        "env": {
          "MEMPHORA_API_KEY": "your_api_key_here"
        }
      }
    }
  }
}

# # Windsurf

Add to your Windsurf MCP configuration:

{
  "mcpServers": {
    "memphora": {
      "command": "python",
      "args": ["-m", "memphora_mcp"],
      "env": {
        "MEMPHORA_API_KEY": "your_api_key_here"
      }
    }
  }
}

# Development

# # Running Locally

#  Clone the repo
git clone https://github.com/Memphora/memphora-mcp.git
cd memphora-mcp

#  Install dependencies
pip install -e ".[dev]"

#  Set your API key
export MEMPHORA_API_KEY="your_key"

#  Run the server
python -m memphora_mcp

# # Testing

pytest tests/

# Privacy & Security

  • Your memories are stored securely in Memphora's cloud
  • Each user has isolated memory storage
  • API keys are stored locally on your machine
  • All communication is encrypted via HTTPS

# Support

# License

MIT License - see LICENSE for details.

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