Memory & MCP 🟡

Memory gives AI long-term memory across sessions. MCP (Model Context Protocol) connects AI to external systems. This chapter explains both mechanisms.

I. Memory System

Memory is a Capability Plugin providing two tools:

• memory_create(content) — write to long-term memory
• memory_search(query) — retrieve from long-term memory

Each Bootstrap automatically searches for memories relevant to the current conversation and injects them into the System Prompt.

Memory Storage

Local vector store (memory-core plugin):

type MemoryEntry = {
  id: string;
  content: string;
  embedding: Float32Array;  // vector embedding via LLM API
  tags: string[];           // agentId, sessionKey, etc.
  createdAt: Date;
  accessedAt: Date;
};

External memory service (memory-mcp plugin) — connects via MCP protocol:

plugins:
  - id: memory-mcp
    mcp:
      command: npx
      args: ['-y', '@mem0/mcp-server']

II. MCP (Model Context Protocol)

MCP is an open protocol by Anthropic allowing AI models to access external tools and data sources through a standardized interface.

Three Integration Modes

Mode 1: mcporter plugin (subprocess, most common):

plugins:
  - id: mcporter
    mcpServers:
      filesystem:
        command: npx
        args: ['-y', '@modelcontextprotocol/server-filesystem', '/workspace']
      github:
        command: npx
        args: ['-y', '@modelcontextprotocol/server-github']
        env:
          GITHUB_TOKEN: "${env:GITHUB_TOKEN}"

Mode 2: Embedded MCP (embedded-pi-mcp.ts) — runs in the same process, no subprocess needed. Used for LSP integration and other in-process tools.

Mode 3: HTTP MCP — connects to remote MCP servers over HTTP.

MCP Tool Registration

After an MCP Server starts, mcporter:

1. Calls tools/list to get the server's tool list
2. Wraps each MCP tool in OpenClaw's tool format (with JSON Schema)
3. Registers via api.tools.register()
4. Agent can call them just like built-in tools

III. Bundle MCP Mode

OpenClaw itself can act as an MCP Server — exposing Agent capabilities to external MCP clients. This enables nesting: another AI application can call OpenClaw agents via MCP.

Key Source Files

Summary

1. Memory plugin provides cross-session memory: memory_create writes, memory_search retrieves, Bootstrap auto-injects relevant memories.
2. Three MCP integration modes: subprocess (mcporter), embedded, remote HTTP.
3. MCP tools integrate transparently: registered as regular agent tools, same usage experience as built-ins.
4. Bundle MCP: OpenClaw itself can be exposed as an MCP Server for multi-layer AI nesting.

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