Resource: thedotmack/claude-mem - Persistent Memory for Claude Code URL: https://github.com/thedotmack/claude-mem Type: Plugin / MCP Server Evaluated: 2026-02-10 Evaluator: Florian BRUNIAUX + Claude (Anthropic)
Score: 4/5 (High Value - Integrate within 1 week)
Claude-mem is a Claude Code plugin providing automatic session memory through AI-compressed capture of tool usage, observations, and decisions. It fills a gap in the guide: while Serena (symbol memory) and grepai (semantic search) are documented, automatic session capture is not.
Key Stats (verified 2026-02-10):
- 26.5k GitHub stars, 1.8k forks
- 181 releases, 46 contributors
- Latest: v9.1.1 (Feb 7, 2026)
- License: AGPL-3.0 + PolyForm Noncommercial
What claude-mem does:
- Automatic Capture: Hooks into Claude Code lifecycle (SessionStart, PostToolUse, Stop, SessionEnd) to record all tool operations
- AI Compression: Uses Claude to generate semantic summaries of observations (~10x token reduction)
- Hybrid Search: Full-text + vector search (Chroma) + natural language queries
- Progressive Disclosure: 3-layer retrieval (search → timeline → get_observations) saves 95% tokens
- Web Dashboard: Real-time UI at
http://localhost:37777for exploring session history - Automatic Injection: Relevant context auto-injected at session start
Architecture:
Lifecycle Hooks → Observation capture → AI compression (Claude)
↓
SQLite storage
↓
Chroma vector indexation
↓
Session start injection
Performance claims (from articles, not independently verified):
- Progressive disclosure: 10x token reduction
- Endless Mode (beta): 95% context reduction → 20x more tool calls before limits
- Cost: ~$0.15 per 100 observations processed
✅ Strengths:
- Gap Identified: Guide documents Serena (symbol memory, manual) and grepai (semantic search) but not automatic session capture
- Massive Adoption: 26.5k stars, 181 releases, 46 active contributors
- Production-Ready: AGPL-3.0 licensed, stable API, active maintenance
- Complementary: Doesn't replace existing tools, enhances them
- Token Efficiency: Progressive disclosure pattern valuable for context management
- Pattern Partially Covered: Serena
write_memory()exists for manual memory, so gap is "automatic" not "memory" - AGPL-3.0 Restrictions: Commercial use limitations, source disclosure requirements
- Hidden Costs: $0.15/100 observations not documented in official README
- CLI Only: No web interface, no cloud sync, no multi-machine support
- Niche Use Case: Benefits users with >10 sessions/week, less valuable for occasional users
| Aspect | This Resource (claude-mem) | Our Guide (v3.23.4) |
|---|---|---|
| Automatic session capture | ✅ Core feature | ❌ Missing |
| Tool usage tracking | ✅ Hooks-based | ➕ Documented (hooks architecture) but no specific tool |
| Progressive disclosure | ✅ 3-layer workflow | ❌ Pattern not documented |
| Session-to-session memory | ✅ Automatic injection | ➕ Partial (Serena manual, not auto) |
| Web dashboard | ✅ Real-time UI | ❌ Missing |
| Token efficiency patterns | ✅ 95% reduction | ➕ Documented (context management) but not this magnitude |
| AGPL licensing implications | ❌ Missing (licensing considerations) | |
| Cost: API compression | ❌ Missing (hidden costs) | |
| Platform limitations | ❌ Missing |
Summary: Guide covers building blocks (hooks, MCP, Serena) but lacks integrated solution that claude-mem provides. Gap is moderate (not critical) because patterns exist, but automatic capture adds significant value.
Recommended: Section 8.2.5 (after grepai) in guide/ultimate-guide.md ~line 8463
Structure:
## 8.2.5 claude-mem (Automatic Session Capture)
### Architecture & Features
- Lifecycle hooks integration
- AI compression workflow
- Progressive disclosure pattern
- Web dashboard overview
### Installation & Setup
- Plugin marketplace installation
- Configuration options
- Privacy controls (<private> tags)
### Usage Patterns
- Automatic injection workflow
- Natural language queries
- Web UI navigation
### Cost & Privacy Considerations
- API compression costs ($0.15/100 obs)
- AGPL-3.0 licensing implications
- Data locality (SQLite + Chroma)
- Privacy tags for sensitive content
### Decision Matrix: vs Serena vs grepai
| Need | Tool | Rationale |
|------|------|-----------|
| Auto capture tool usage | claude-mem | Zero manual effort |
| Symbol-aware navigation | Serena | Precise editing |
| Semantic discovery | grepai | Intent-based search |
| Manual decision storage | Serena | Explicit control |
### Hybrid Workflows
- claude-mem + Serena (auto capture + manual decisions)
- claude-mem + grepai (session history + semantic search)
- Complete stack: rg → grepai → Serena → claude-memSize: 300-400 lines (not 800 as initially proposed)
-
guide/ultimate-guide.md
- Add Section 8.2.5 (~300 lines)
- Update Section 2.2 (Session vs Persistent Memory) with claude-mem reference
-
machine-readable/reference.yaml
claude_mem: "guide/ultimate-guide.md:8463" claude_mem_architecture: "guide/ultimate-guide.md:8470" claude_mem_progressive_disclosure: "guide/ultimate-guide.md:8520" claude_mem_dashboard: "guide/ultimate-guide.md:8550" claude_mem_vs_serena: "guide/ultimate-guide.md:8600" claude_mem_installation: "/plugin marketplace add thedotmack/claude-mem" claude_mem_repo: "https://github.com/thedotmack/claude-mem" claude_mem_stars: "26.5k" claude_mem_license: "AGPL-3.0" claude_mem_score: "4/5"
-
examples/plugins/claude-mem.md (installation template)
-
CHANGELOG.md
## [3.24.0] - 2026-02-XX ### Added - **Section 8.2.5**: claude-mem plugin documentation - Memory Stack Patterns (claude-mem + Serena + grepai integration) - Decision matrix for memory tools
High Value - Integrate within 1 week
Rationale:
- Fills genuine gap (automatic capture not documented)
- Massive community adoption (26.5k stars)
- Complementary to existing tools
- BUT not "Critical" (5/5) because patterns partially exist
| Aspect | claude-mem | Serena | grepai |
|---|---|---|---|
| Purpose | Session capture | Symbol memory | Semantic search |
| Trigger | Auto (hooks) | Manual API | Manual CLI |
| Storage | SQLite + Chroma | .serena/memories/ |
Ollama vectors |
| Technology | AI compression | Key-value store | Embeddings |
| Indexation | Session events | Project symbols | Code files |
| Query | Natural language | Key lookup | Semantic search |
| Dashboard | ✅ Web UI | ❌ No | ❌ No |
| Cost | $0.15/100 obs | Free (local) | Free (local) |
| Privacy | ✅ Local | ✅ Local | ✅ Local |
| Need | Tool | Example |
|---|---|---|
| "What did we do yesterday?" | claude-mem | Auto-inject previous context |
| "Find function login" | Serena | find_symbol --name "login" |
| "Who calls this function?" | grepai | grepai trace callers "login" |
| "Record arch decision" | Serena | write_memory("auth", "JWT") |
| "Find code that does X" | grepai | grepai search "payment validation" |
| "Summary of all sessions" | claude-mem | Web dashboard + search |
| "Exact pattern 'authenticate'" | rg (native) | rg "authenticate" --type ts |
┌─────────────────────────────────────────────────────────┐
│ Memory Stack (4 layers) │
├─────────────────────────────────────────────────────────┤
│ Layer 4: Session Capture → claude-mem (automatic) │
│ Layer 3: Symbol Memory → Serena (manual decisions) │
│ Layer 2: Semantic Search → grepai (discovery) │
│ Layer 1: Exact Search → rg (native, fast) │
└─────────────────────────────────────────────────────────┘
Integrated Workflow Example:
# Scenario: Refactoring auth module after 3 days
# 1. AUTO CONTEXT (claude-mem)
# At session start, Claude injects:
# "3 previous sessions explored auth module.
# Decision: Migrate to JWT.
# Files modified: auth.service.ts, session.middleware.ts"
# 2. ARCH DECISIONS (Serena)
serena list_memories
# → "auth_decision: Use JWT for stateless API (2026-02-07)"
serena read_memory("auth_decision")
# 3. SEMANTIC DISCOVERY (grepai)
grepai search "JWT token validation"
# → Finds validateJWT() in auth.service.ts
# 4. DEPENDENCIES (grepai trace)
grepai trace callers "validateJWT"
# → Called by: ApiGateway, AdminPanel, UserController
# 5. EXACT SEARCH (rg)
rg "validateJWT" --type ts -A 5Result: Complete context without re-reading all files, safe refactoring.
| Claim | Source | Verified | Notes |
|---|---|---|---|
| 26.5k stars | GitHub (WebFetch 2026-02-10) | ✅ | Perplexity had 15.6k (outdated) |
| 1.8k forks | GitHub | ✅ | Confirmed |
| 181 releases | GitHub | ✅ | Perplexity had 174 (outdated) |
| 46 contributors | GitHub | ✅ | Perplexity had 22 (outdated) |
| AGPL-3.0 license | GitHub README | ✅ | + PolyForm Noncommercial for ragtime/ |
| Latest: v9.1.1 (Feb 7, 2026) | GitHub releases | ✅ | Active |
| Target: Claude Code | GitHub README | ✅ | Primary (+ Desktop secondary support) |
| Guide doesn't document Serena | ultimate-guide.md grep | ❌ FALSE | 10 occurrences found |
| Guide doesn't document grepai | ultimate-guide.md grep | ❌ FALSE | 22 occurrences found |
| Progressive disclosure 10x | Perplexity + articles | Claim verified but metric approximate | |
| $0.15/100 observations | External articles | Not found in official README | |
| 95% Endless Mode | Articles | Beta claim, not independently verified |
Corrections Applied:
-
Gap analysis corrected: Guide DOES document Serena (lines 686, 762, 765, 770, 775, 779, 968, 1521, 1532) and grepai (22 mentions). Gap is not "no memory docs" but "no automatic capture solution".
-
Stats verified: 26.5k stars (Perplexity outdated), 181 releases, 46 contributors.
-
Product target: Claude Code (primary), not confused with Desktop.
-
Perplexity reliability: Detected outdated data → always verify GitHub directly for critical stats.
-
AGPL-3.0 License
- Modifications require source disclosure
- Network deployment requires AGPL
- Commercial use restrictions
-
Hidden Costs
- $0.15 per 100 observations (API compression)
- Not documented in official README
- Can accumulate on large projects
-
CLI Only
- No web interface support
- No cloud sync between machines
- No VS Code integration
-
Manual Privacy Tags
<private>tags required for sensitive content- Forgetting tags → sensitive data in DB
- No automatic secret detection
Guide already documents:
- Session search (
guide/observability.md:29) - Session migration (
guide/observability.md:175) - Context management (
/compact,/clear)
Question: Does claude-mem provide enough incremental value to justify 300-400 lines?
Answer: Yes, because:
- ✅ Automatic capture (vs manual Serena)
- ✅ AI compression (vs raw sessions)
- ✅ Web dashboard (vs CLI only)
- ✅ Progressive disclosure (token efficiency)
Agent ID: ac8e0c6
Challenge Summary:
The technical-writer agent challenged the initial 5/5 score, identifying:
- False premise: "Guide doesn't document Serena/grepai" → FALSE (both documented)
- Stats contradictions: 15.6k vs 26.5k stars → Required verification
- Product confusion: Clarified Claude Code vs Claude Desktop targeting
- Sizing issues: 800 lines over-dimensioned → Reduced to 300-400 lines
- Urgency questioned: <24h unrealistic → Changed to 1 week
Result: Score adjusted from 5/5 → 4/5 based on:
- Gap is real but moderate (Serena/grepai exist, automatic capture missing)
- AGPL-3.0 + hidden costs + CLI-only = limitations
- Complementary tool, not critical infrastructure
Articles:
- Corti.com: Claude-Mem Deep Dive (2026-02-03)
- yuv.ai: Persistent Memory Guide (2026-02-05)
- byteiota: Progressive Disclosure Analysis (2026-02-04)
Videos:
- YouTube: 5-Minute Setup Guide (2026-02-06)
- YouTube: Unlimited Memory Demo (2026-02-05)
GitHub:
Benchmarks:
- No independent benchmarks found as of 2026-02-10
- Claims from articles: "95% context reduction, 20x tool calls" (not verified)
- Progressive disclosure: "10x token reduction" (plausible based on architecture)
Score: 4/5 (High Value - Integrate within 1 week)
Action:
- Integrate Section 8.2.5 in
guide/ultimate-guide.md(300-400 lines) - Update
machine-readable/reference.yamlwith claude-mem entries - Create plugin template in
examples/plugins/claude-mem.md - Add to CHANGELOG.md v3.24.0
Confidence: High (stats verified, architecture understood, integration plan clear)
Evaluated: 2026-02-10 Next Review: Before v3.24.0 integration Status: Approved for integration