agentmemory

name	agentmemory
description	Persistent cross-session memory for AI coding agents. Use when working across multiple sessions, recalling past context, saving decisions, or searching historical observations.

Agentmemory Skill

Provides persistent memory capabilities for coding agents using the agentmemory MCP server.

When to Activate

• Starting a new session that builds on previous work
• User asks "remember this", "do you recall", "what did we do last time"
• Before making architectural decisions that past context could inform
• After discovering a bug, to save the pattern for future prevention
• After making a design decision, to persist the rationale
• When the user asks about project history or session timeline

Core Tools

memory_save

Save an insight, decision, or fact to long-term memory.

memory_save(
  content: "We chose jose over jsonwebtoken for Edge Runtime compatibility",
  concepts: ["jwt-auth", "edge-runtime", "jose-library", "auth-middleware"],
  files: ["src/middleware/auth.ts"],
  type: "architecture"
)

memory_recall

Search past observations by exact keywords.

memory_recall(query: "jwt auth setup", limit: 5)

memory_smart_search

Hybrid semantic+keyword search. Use for fuzzy or conceptual queries.

memory_smart_search(query: "how did we handle database performance", limit: 10)

memory_sessions

List recent sessions with status and observation counts.

memory_sessions(limit: 10)

memory_file_history

Get past observations about specific files across all sessions. Call before editing a file.

memory_file_history(files: ["src/middleware/auth.ts"])

memory_lesson_save / memory_lesson_recall

Save and retrieve lessons learned with confidence scoring.

memory_lesson_save(
  content: "Always validate JWT expiry before decoding payload",
  concepts: ["jwt-validation", "security"],
  domain: "backend"
)
memory_lesson_recall(query: "jwt security", limit: 5)

memory_governance_delete

Delete specific memories. Requires explicit user confirmation.

memory_patterns

Detect recurring patterns across sessions.

memory_consolidate

Run the 4-tier memory consolidation pipeline.

Behavior Rules

1. Proactive recall: Before implementing new features or fixing bugs, check agentmemory for relevant past context.
2. Auto-save: After discovering a bug, making an architectural decision, or learning a project convention, save it.
3. Session awareness: Use memory_sessions when the user asks about project history or past work.
4. File context: Use memory_file_history before editing files to surface past issues or decisions about that file.
5. Never hallucinate: Only present what the MCP tools return. Report "no results found" when appropriate.
6. Tool prefix: All agentmemory tools use the agentmemory_memory_ prefix in the tool list. Use the exact names as listed.

Integration Notes

• Server runs on http://localhost:3111 by default
• Real-time viewer at http://localhost:3113
• Start the server with npx @agentmemory/agentmemory
• 53 MCP tools available when server is running
• 22 auto-capture hooks via plugin record session lifecycle automatically