MemoryLake
Engineering & Developer

Add Persistent Memory to Any MCP-Compatible AI Tool

The Model Context Protocol gives AI tools a standard way to call external systems. MemoryLake uses that standard to make structured persistent memory available to any MCP-compatible tool — with no custom integration code required.

DAY 1 · WITHOUT MEMORYThe Model Context Protocol gives AI tools a standard way to call external sys…Got it, I'll remember.DAY 7 · NEW SESSIONSame task, please?Sure — what was the context again?(forgot every detail you taught it)WITH MEMORYLAKEMemory auto-loadedSix typed memory categories available…Memory accumulation during the sessionMCP differs from REST API in scope an…SESSION OUTPUTSame prompt, on-brand answerGet Started Free →

Add Persistent Memory to Any MCP-Compatible AI Tool

Get Started Free

Free forever · No credit card required

The Memory Problem

MCP-compatible tools like Claude Code and OpenClaw are powerful within a session, but that session ends. The next time you open the tool, the accumulated context — decisions made, approaches that worked, project-specific facts — is gone. MCP can connect to external systems, but most tools don't provide a memory system worth connecting to. MemoryLake is that system.

What MemoryLake Does Differently

Six typed memory categories available at session start — When your MCP tool connects to MemoryLake at session open, relevant Background Memory (identity, preferences, role context) and recent Conversation Memory are surfaced immediately, giving the session a warm start with zero manual setup.

Memory accumulation during the session — As work progresses, the tool writes to appropriate memory categories: new facts to Fact Memory, completed approaches to Skill Memory, behavioral patterns to Reflection Memory. Memory compounds with every session.

MCP differs from REST API in scope and trigger — REST API integration is best for application-level memory management — bulk operations, cross-user queries, administrative access. MCP integration is optimized for session-level, real-time memory read/write during a live agent interaction. Both protocols are supported simultaneously.

DAY 1 · WITHOUT MEMORYThe Model Context Protocol gives AI tools a standard way to call external sys…Got it, I'll remember.DAY 7 · NEW SESSIONSame task, please?Sure — what was the context again?(forgot every detail you taught it)WITH MEMORYLAKEMemory auto-loadedSix typed memory categories available…Memory accumulation during the sessionMCP differs from REST API in scope an…SESSION OUTPUTSame prompt, on-brand answerGet Started Free →

Add Persistent Memory to Any MCP-Compatible AI Tool

Get Started Free

Free forever · No credit card required

How It Works

  1. Connect — Add MemoryLake as an MCP server in your tool's configuration. Provide your API key and memory store identifier. The MCP server handles authentication and routing.
  2. Structure — At session start, MemoryLake surfaces relevant memory by type. During the session, the tool writes to memory categories as directed. All writes are versioned and source-attributed automatically.
  3. Reuse — The next session opens with the accumulated memory from all prior sessions. The tool remembers your preferences, project state, working patterns, and prior decisions without any manual context management.

Before & After

Without MemoryLake MCPWith MemoryLake MCP
Session startCold — no prior contextBackground + Conversation Memory loaded automatically
Project contextRe-explained each sessionStored in Fact and Event Memory, retrieved on demand
Working preferencesRe-stated or hardcoded in promptsBackground Memory surfaces them at session open
Learned workflowsRediscovered each timeSkill Memory persists and retrieves them automatically
Audit trailNoneEvery memory operation versioned with timestamp and source

Built For

MemoryLake MCP integration is designed for developers and technical users who rely on MCP-compatible tools daily and want those tools to accumulate knowledge rather than reset. It works with Claude Code, OpenClaw, and any agent framework that implements the Model Context Protocol.

Related use cases

Frequently asked questions

How do I register MemoryLake as an MCP server?

Add the MemoryLake MCP server endpoint to your tool's MCP configuration with your API key. The exact configuration format follows the standard MCP server registration pattern. Full setup instructions are in the MemoryLake developer docs.

Can I use MCP and REST API at the same time?

Yes. MCP handles real-time, session-level memory operations during live agent interactions. REST API handles administrative, bulk, and cross-session operations. They operate on the same underlying memory store.

Which memory types are accessible via MCP?

All six memory types are accessible via MCP: Background, Fact, Event, Conversation, Reflection, and Skill. The MCP server exposes read and write operations for each type, with role-based access control applied per memory type.