Membase MCP: Persistent Memory for AI Agents That Actually Remembers

Your AI agents forget everything the moment a session ends. Every conversation starts from scratch, losing valuable context, personalization, and learned insights. You end up repeating the same setup instructions, re-explaining project context, and rebuilding rapport with your AI assistant daily.

Membase MCP changes that. It's a decentralized memory layer that gives your AI agents persistent, verifiable memory across all sessions.

The Memory Problem Every Developer Faces

You spend 10 minutes every morning re-briefing Claude about your project architecture, coding standards, and current focus areas. Yesterday's brilliant insights? Gone. The context you built up over weeks of conversations? Vanished. Your AI assistant has digital amnesia, and it's killing your productivity.

Traditional solutions either don't exist or lock you into proprietary platforms with zero portability. Membase MCP runs on the Unibase decentralized network, giving you:

• Session Continuity: Pick up exactly where you left off, every time
• Verifiable Storage: Your conversation history is cryptographically secured
• Cross-Tool Memory: Same memory layer works across Claude, Cursor, Windsurf, and Cline
• Decentralized Ownership: Your data isn't trapped in someone else's silo

Four Functions That Change Everything

# Get your current conversation context
get_conversation_id()

# Switch between different project conversations  
switch_conversation("mobile-app-project")

# Save important insights and decisions
save_message("Decided to use React Native with Expo for faster prototyping")

# Retrieve relevant context when you need it
get_messages(n=20)  # Last 20 messages with full context

Real-World Impact

Before Membase MCP: "Hey Claude, I'm working on a Python API that uses FastAPI and PostgreSQL. We decided yesterday to implement JWT authentication and use SQLAlchemy for the ORM. The database schema has users, projects, and tasks tables with foreign key relationships..."

After Membase MCP: "Let's continue building the authentication middleware we discussed yesterday."

Your AI immediately knows your tech stack, previous decisions, coding patterns, and project context. No repetition, no context loss, just continuous productive conversation.

Integration in 2 Minutes

Add it to your Claude/Cursor/Windsurf config:

{
  "mcpServers": {
    "membase": {
      "command": "uv",
      "args": ["--directory", "path/to/membase-mcp", "run", "src/membase_mcp/server.py"],
      "env": {
        "MEMBASE_ACCOUNT": "0x...",
        "MEMBASE_CONVERSATION_ID": "my-project-conversations", 
        "MEMBASE_ID": "dev-instance"
      }
    }
  }
}

Clone the repo, set your environment variables, and you're running. No complex setup, no API keys to manage, no vendor lock-in.

Multiple Project Conversations

Managing different codebases or client projects? Create separate conversation threads for each:

• mobile-app-redesign - All conversations about the iOS/Android rewrite
• api-v2-migration - Backend modernization discussions
• client-dashboard - Frontend work for the analytics dashboard

Switch between them instantly while maintaining full context for each project.

Decentralized by Design

Your conversation history lives on the Unibase network, not in some company's database that could disappear tomorrow. It's verifiable, portable, and truly yours. View your stored conversations at https://testnet.hub.membase.io/ and see the cryptographic proofs of every interaction.

This isn't just another memory solution - it's infrastructure for AI agents that remember, learn, and grow with your projects instead of starting fresh every day.

Get started: git clone https://github.com/unibaseio/membase-mcp.git