Membase MCP Server

Overview

Membase is a decentralized memory layer designed to give AI agents persistent, secure, and verifiable storage for everything that matters in a conversation: chat history, interaction logs, and domain knowledge. By leveraging the Unibase Distributed Autonomous (DA) network, Membase removes the reliance on centralized databases and offers agents a tamper‑proof record of their interactions. This continuity is critical for building personalized experiences, maintaining context across sessions, and ensuring auditability in regulated environments.

The Membase‑MCP server exposes a small but powerful set of functions that let an AI assistant read from and write to this distributed memory. Developers can fetch the current conversation ID, switch between multiple conversations, store a new message or “memoir” in the active conversation, and retrieve recent messages. These primitives enable agents to seamlessly persist context between runs, load historical state when a user resumes a dialogue, and share knowledge across multiple instances without duplicating data.

Key features include:

• Decentralized persistence – Messages are stored on the Unibase DA network, providing resilience against single points of failure and ensuring data integrity through cryptographic verification.
• Conversation management – The server tracks a unique conversation ID, allowing agents to isolate context and support multi‑threaded dialogue flows.
• Simple CRUD operations – With and , agents can append new content and pull recent history with minimal overhead.
• Secure account handling – Environment variables let developers bind a specific Unibase account, conversation ID, and instance identifier, keeping data isolated per user or application.

In practice, Membase shines in scenarios where continuity and traceability are paramount. For example, a customer‑support bot can retrieve a user’s prior inquiries to provide consistent answers, while an educational tutor can recall past lessons to personalize subsequent sessions. Regulatory compliance teams can audit agent behavior by inspecting the immutable conversation logs stored on the DA network.

Integrating Membase into an AI workflow is straightforward: configure the MCP server with the appropriate environment variables, add it to your assistant’s list, and invoke the provided functions during dialogue. The server acts as a bridge between the agent’s runtime memory and a durable, decentralized store, giving developers confidence that context is never lost and can be verified independently.