XzhLoongSkills/skills/agency-agents/integrations/mcp-memory

MCP Memory Integration

Give any agent persistent memory across sessions using the Model Context Protocol (MCP).

What It Does

By default, agents in The Agency start every session from scratch. Context is passed manually via copy-paste between agents and sessions. An MCP memory server changes that:

• Cross-session memory: An agent remembers decisions, deliverables, and context from previous sessions
• Handoff continuity: When one agent hands off to another, the receiving agent can recall exactly what was done — no copy-paste required
• Rollback on failure: When a QA check fails or an architecture decision turns out wrong, roll back to a known-good state instead of starting over

Setup

You need an MCP server that provides memory tools: remember, recall, rollback, and search. Add it to your MCP client config (Claude Code, Cursor, etc.):

{
  "mcpServers": {
    "memory": {
      "command": "your-mcp-memory-server",
      "args": []
    }
  }
}

Any MCP server that exposes remember, recall, rollback, and search tools will work. Check the MCP ecosystem for available implementations.

How to Add Memory to Any Agent

To enhance an existing agent with persistent memory, add a Memory Integration section to the agent's prompt. This section instructs the agent to use MCP memory tools at key moments.

The Pattern

## Memory Integration

When you start a session:
- Recall relevant context from previous sessions using your role and the current project as search terms
- Review any memories tagged with your agent name to pick up where you left off

When you make key decisions or complete deliverables:
- Remember the decision or deliverable with descriptive tags (your agent name, the project, the topic)
- Include enough context that a future session — or a different agent — can understand what was done and why

When handing off to another agent:
- Remember your deliverables tagged for the receiving agent
- Include the handoff metadata: what you completed, what's pending, and what the next agent needs to know

When something fails and you need to recover:
- Search for the last known-good state
- Use rollback to restore to that point rather than rebuilding from scratch

What the Agent Does With This

The LLM will use MCP memory tools automatically when given these instructions:

• remember — store a decision, deliverable, or context snapshot with tags
• recall — search for relevant memories by keyword, tag, or semantic similarity
• rollback — revert to a previous state when something goes wrong
• search — find specific memories across sessions and agents

No code changes to the agent files. No API calls to write. The MCP tools handle everything.

Example: Enhancing the Backend Architect

See backend-architect-with-memory.md for a complete example — the standard Backend Architect agent with a Memory Integration section added.

Example: Memory-Powered Workflow

See ../../examples/workflow-with-memory.md for the Startup MVP workflow enhanced with persistent memory, showing how agents pass context through memory instead of copy-paste.

Tips

• Tag consistently: Use the agent name and project name as tags on every memory. This makes recall reliable.
• Let the LLM decide what's important: The memory instructions are guidance, not rigid rules. The LLM will figure out when to remember and what to recall.
• Rollback is the killer feature: When a Reality Checker fails a deliverable, the original agent can roll back to its last checkpoint instead of trying to manually undo changes.