memory-mcp

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Persistent memory for Claude Code with two-tier architecture: hot cache for instant recall (0ms) and semantic search for everything else (~50ms). Automatically learns what you use and promotes it.

michael-denyer By michael-denyer schedule Updated 1/23/2026

name: memory-mcp description: > Persistent memory for Claude Code with two-tier architecture: hot cache for instant recall (0ms) and semantic search for everything else (~50ms). Automatically learns what you use and promotes it. allowed-tools: "mcp__memory__*" version: "0.6.0" author: "Michael Denyer https://github.com/michael-denyer" license: "MIT"

Memory MCP - Persistent Memory for Claude Code

Give your AI assistant a second brain that persists across sessions.

Two-Tier Architecture

Tier Latency How it works
Hot Cache 0ms Auto-injected into context before Claude thinks
Cold Storage ~50ms Semantic search via recall() tool call

The system learns what you use and automatically promotes frequently-accessed memories to the hot cache.

Quick Start

Store a Memory

remember("FastAPI with async endpoints for all APIs", memory_type="project", tags=["tech-stack"])

Recall by Meaning

recall("what framework for backend")  # Finds FastAPI memory

Check What's Hot

hot_cache_status()  # See what's instantly available

Core Tools

Storage

Tool Purpose
remember(content, memory_type, tags) Store new memory
recall(query, mode, limit) Semantic search
recall_by_tag(tag) Find by tag
forget(memory_id) Delete memory
list_memories(limit, offset) Browse all

Memory types: project, pattern, reference, episodic, conversation

Recall modes: precision (few, high-confidence), balanced (default), exploratory (many results)

Hot Cache

Tool Purpose
promote(memory_id) Add to hot cache
demote(memory_id) Remove from hot cache
pin(memory_id) Prevent auto-eviction
unpin(memory_id) Allow auto-eviction
hot_cache_status() View hot cache contents

Knowledge Graph

Tool Purpose
link_memories(from_id, to_id, relation) Connect memories
unlink_memories(from_id, to_id) Remove connection
get_related_memories(memory_id) Find connected
relationship_stats() Graph overview

Relation types: relates_to, depends_on, supersedes, refines, contradicts, elaborates

Trust Management

Tool Purpose
validate_memory(id, reason) Increase trust
invalidate_memory(id, reason) Decrease trust
get_trust_history(memory_id) View changes

Sessions

Tool Purpose
get_sessions() List sessions
summarize_session(session_id) Structured summary
end_session(session_id) Promote top memories

Pattern Mining

Tool Purpose
mining_status() View mining stats
review_candidates() See patterns found
approve_candidate(id) Promote to memory
reject_candidate(id) Discard pattern

Maintenance

Tool Purpose
memory_stats() Overview stats
db_info() Database details
run_cleanup() Clean stale data
preview_consolidation() Find duplicates

MCP Resources

These are auto-injected into Claude's context:

Resource Contents
memory://hot-cache All promoted memories
memory://working-set Session-aware context (~10 items)
memory://project-context Current project memories

Auto-Promotion Rules

Memories are auto-promoted to hot cache when:

  • Salience score ≥ 0.5 AND access count ≥ 3
  • Salience = importance + trust + access_count + recency

Memories are auto-demoted after 14 days without access.

Common Workflows

Project Setup

# Bootstrap from project docs (CLAUDE.md, README.md, etc.)
bootstrap_project(promote_to_hot=true)

Daily Work

# Store decisions and patterns as you work
remember("Decided to use PostgreSQL for main DB", memory_type="project", tags=["decision", "database"])

# Recall when needed
recall("database decision")

Session End

# Review what you learned
summarize_session(session_id)

# Promote valuable memories to long-term storage
end_session(session_id, promote_top=true)

Knowledge Linking

# Connect related concepts
link_memories(postgres_id, pgvector_id, "depends_on")

# Recall with graph expansion
recall("PostgreSQL", expand_relations=true)

Tips

  1. Tag consistently - Use tags like decision, convention, tech-stack, gotcha
  2. Use episodic for session context - Short-term memories that may get promoted
  3. Link related memories - Build a knowledge graph for better recall
  4. Trust the auto-promotion - Don't over-promote manually
  5. Check hot cache periodically - hot_cache_status() shows what's instantly available
Install via CLI
npx skills add https://github.com/michael-denyer/memory-mcp --skill memory-mcp
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