MCP Memory Service

Stop Re-Explaining Your Project to AI Every Session

Your AI assistant forgets everything when you start a new chat. After 50 tool uses, context explodes to 500k+ tokens—Claude slows down, you restart, and now it remembers nothing. You spend 10 minutes re-explaining your architecture. Again.

MCP Memory Service solves this.

It automatically captures your project context, architecture decisions, and code patterns. When you start fresh sessions, your AI already knows everything—no re-explaining, no context loss, no wasted time.

⚡ Works With Your Favorite AI Tools

🖥️ CLI & Terminal AI

Claude Code · Gemini Code Assist · Aider · GitHub Copilot CLI · Amp · Continue · Zed · Cody

🎨 Desktop & IDE

Claude Desktop · VS Code · Cursor · Windsurf · Raycast · JetBrains · Sourcegraph · Qodo

Works seamlessly with any MCP-compatible client - whether you code in the terminal, IDE, or browser.

🚀 Get Started in 60 Seconds

Express Install (recommended for most users):

pip install mcp-memory-service
# Auto-configure for Claude Desktop (macOS/Linux)
python -m mcp_memory_service.scripts.installation.install --quick

What just happened?

✅ Installed memory service
✅ Configured optimal backend (SQLite)
✅ Set up Claude Desktop integration
✅ Enabled automatic context capture

Next: Restart Claude Desktop. Your AI now remembers everything across sessions.

📦 Alternative: PyPI + Manual Configuration

pip install mcp-memory-service

Then add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

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

🔧 Advanced: Custom Backends & Team Setup

For production deployments, team collaboration, or cloud sync:

git clone https://github.com/doobidoo/mcp-memory-service.git
cd mcp-memory-service
python scripts/installation/install.py

Choose from:

SQLite (local, fast, single-user)
Cloudflare (cloud, multi-device sync)
Hybrid (best of both: 5ms local + background cloud sync)

💡 Why You Need This

The Problem

Session 1	Session 2 (Fresh Start)
You: "We're building a Next.js app with Prisma and tRPC"	AI: "What's your tech stack?" ❌
AI: "Got it, I see you're using App Router"	You: Explains architecture again for 10 minutes 😤
You: "Add authentication with NextAuth"	AI: "Should I use Pages Router or App Router?" ❌

The Solution

Session 1	Session 2 (Fresh Start)
You: "We're building a Next.js app with Prisma and tRPC"	AI: "I remember—Next.js App Router with Prisma and tRPC. What should we build?" ✅
AI: "Got it, I see you're using App Router"	You: "Add OAuth login"
You: "Add authentication with NextAuth"	AI: "I'll integrate NextAuth with your existing Prisma setup." ✅

Result: Zero re-explaining. Zero context loss. Just continuous, intelligent collaboration.

🌐 SHODH Ecosystem Compatibility

MCP Memory Service is fully compatible with the SHODH Unified Memory API Specification v1.0.0, enabling seamless interoperability across the SHODH ecosystem.

Compatible Implementations

Implementation	Backend	Embeddings	Use Case
shodh-memory	RocksDB	MiniLM-L6-v2 (ONNX)	Reference implementation
shodh-cloudflare	Cloudflare Workers + Vectorize	Workers AI (bge-small)	Edge deployment, multi-device sync
mcp-memory-service (this)	SQLite-vec / Hybrid	MiniLM-L6-v2 (ONNX)	Desktop AI assistants (MCP)

Unified Schema Support

All SHODH implementations share the same memory schema:

✅ Emotional Metadata: emotion, emotional_valence, emotional_arousal
✅ Episodic Memory: episode_id, sequence_number, preceding_memory_id
✅ Source Tracking: source_type, credibility
✅ Quality Scoring: quality_score, access_count, last_accessed_at

Interoperability Example: Export memories from mcp-memory-service → Import to shodh-cloudflare → Sync across devices → Full fidelity preservation of emotional_valence, episode_id, and all spec fields.

✨ Quick Start Features

🧠 Persistent Memory – Context survives across sessions with semantic search 🔍 Smart Retrieval – Finds relevant context automatically using AI embeddings ⚡ 5ms Speed – Instant context injection, no latency 🔄 Multi-Client – Works across 13+ AI applications ☁️ Cloud Sync – Optional Cloudflare backend for team collaboration 🔒 Privacy-First – Local-first, you control your data 📊 Web Dashboard – Visualize and manage memories at http://localhost:8000 🧬 Knowledge Graph – Interactive D3.js visualization of memory relationships 🆕

🖥️ Dashboard Preview (v9.3.0)

Dashboard	Quality Analytics	Browse Tags

8 Dashboard Tabs: Dashboard • Search • Browse • Documents • Manage • Analytics • Quality (NEW) • API Docs

📖 See Web Dashboard Guide for complete documentation.

🆕 Latest Release: v10.1.0 (January 25, 2026)

NEW FEATURE: Python 3.14 Support

What's New:

🐍 Python 3.14 Compatibility: Expanded Python support from 3.10-3.13 to 3.10-3.14
📦 Tokenizers Upgrade: Updated to >=0.22.2 (resolves PyO3 compatibility issues)
🔄 Zero Breaking Changes: Full backward compatibility maintained across all Python versions
✅ 1005 Tests Passing: All tests verified across Python 3.10-3.14

Previous Releases:

v10.0.3 - CRITICAL FIX: Backup Scheduler Now Works (2 critical bugs fixed, FastAPI lifespan integration)
v10.0.2 - Tool List Cleanup (Only 12 unified tools visible, 64% tool reduction complete)
v10.0.1 - CRITICAL HOTFIX: MCP tools loading restored (Python boolean fix)
v10.0.0 - ⚠️ BROKEN: Major API Redesign (64% Tool Consolidation) - Tools failed to load, use v10.0.2 instead
v9.3.1 - Critical shutdown bug fix (SIGTERM/SIGINT handling, clean server termination)
v9.3.0 - Relationship Inference Engine (Intelligent association typing, multi-factor analysis, confidence scoring)
v9.2.1 - Critical Knowledge Graph bug fix (MigrationRunner, 37 test fixes, idempotent migrations)
v9.2.0 - Knowledge Graph Dashboard with D3.js v7.9.0 (Interactive force-directed visualization, 6 typed relationships, 7-language support)
v9.0.6 - OAuth Persistent Storage Backend (SQLite-based for multi-worker deployments, <10ms token operations)
v9.0.5 - CRITICAL HOTFIX: OAuth 2.1 token endpoint routing bug fixed (HTTP 422 errors eliminated)
v9.0.4 - OAuth validation blocking server startup fixed (OAUTH_ENABLED default changed to False, validation made non-fatal)
v9.0.2 - Critical hotfix: Includes actual code fix for mass deletion bug (confirm_count parameter now REQUIRED)
v9.0.1 - Incorrectly tagged release (⚠️ Does NOT contain fix - use v9.0.2 instead)
v9.0.0 - Phase 0 Ontology Foundation (⚠️ Contains critical bug - upgrade to v9.0.2 immediately)
v8.76.0 - Official Lite Distribution (90% size reduction: 7.7GB → 805MB, dual publishing workflow)
v8.75.1 - Hook Installer Fix (flexible MCP server naming support, custom configurations)
v8.75.0 - Lightweight ONNX Quality Scoring (90% installation size reduction: 7.7GB → 805MB, same quality scoring performance)
v8.74.0 - Cross-Platform Orphan Process Cleanup (database lock prevention, automatic orphan detection after crashes)
v8.73.0 - Universal Permission Request Hook (auto-approves safe operations, eliminates repetitive prompts for 12+ tools)
v8.72.0 - Graph Traversal MCP Tools (find_connected_memories, find_shortest_path, get_memory_subgraph - 5-25ms, 30x faster)
v8.71.0 - Memory Management APIs and Graceful Shutdown (cache cleanup, process monitoring, production-ready memory management)
v8.70.0 - User Override Commands for Memory Hooks (#skip/#remember for manual memory control)
v8.69.0 - MCP Tool Annotations for Improved LLM Decision-Making (readOnlyHint/destructiveHint, auto-approval for 12 tools)
v8.68.2 - Platform Detection Improvements (Apple Silicon MPS support, 3-5x faster, comprehensive hardware detection)
v8.68.1 - Critical Data Integrity Bug Fix - Hybrid Backend (ghost memories fixed, 5 method fixes)
v8.68.0 - Update & Restart Automation (87% time reduction, <2 min workflow, cross-platform scripts)
v8.62.13 - HTTP-MCP Bridge API Endpoint Fix (Remote deployments restored with POST endpoints)
v8.62.12 - Quality Analytics UI Fixed ("Invalid Date" and "ID: undefined" bugs)
v8.62.10 - Document Ingestion Bug Fixed (NameError in web console, circular import prevention)
v8.62.8 - Environment Configuration Loading Bug Fixed (.env discovery, python-dotenv dependency)
v8.62.7 - Windows SessionStart Hook Bug Fixed in Claude Code 2.0.76+ (no more Windows hanging)
v8.62.6 - CRITICAL PRODUCTION HOTFIX: SQLite Pragmas Container Restart Bug (database locking errors after container restarts)
v8.62.5 - Test Suite Stability: 40 Tests Fixed (99% pass rate, 68% → 99% improvement)
v8.62.4 - CRITICAL BUGFIX: SQLite-Vec KNN Syntax Error (semantic search completely broken on sqlite-vec/hybrid backends)
v8.62.3 - CRITICAL BUGFIX: Memory Recall Handler Import Error (time_parser import path correction)
v8.62.2 - Test Infrastructure Improvements (5 test failures resolved, consolidation & performance suite stability)
v8.62.1 - Critical Bug Fix: SessionEnd Hook Real Conversation Data (hardcoded mock data fix, robust transcript parsing)
v8.62.0 - Comprehensive Test Coverage Infrastructure - 100% Handler Coverage Achievement (35 tests, 800+ lines, CI/CD gate)
v8.61.2 - CRITICAL HOTFIX: delete_memory KeyError Fix (response parsing, validated delete flow)
v8.61.1 - CRITICAL HOTFIX: Import Error Fix (5 MCP tools restored, relative import path correction)
v8.60.0 - Health Check Strategy Pattern Refactoring - Phase 3.1 (78% complexity reduction, Strategy pattern)
v8.59.0 - Server Architecture Refactoring - Phase 2 (40% code reduction, 29 handlers extracted, 5 specialized modules)
v8.58.0 - Test Infrastructure Stabilization - 100% Pass Rate Achievement (81.6% → 100%, 52 tests fixed)
v8.57.1 - Hotfix: Python -m Execution Support for CI/CD (server/main.py, --version/--help flags)
v8.57.0 - Test Infrastructure Improvements - Major Stability Boost (+6% pass rate, 32 tests fixed)
v8.56.0 - Server Architecture Refactoring - Phase 1 (4 focused modules, -7% lines, backward compatible)
v8.55.0 - AI-Optimized MCP Tool Descriptions (30-50% reduction in incorrect tool selection)
v8.54.4 - Critical MCP Tool Bugfix (check_database_health method call correction)
v8.54.3 - Chunked Storage Error Reporting Fix (accurate failure messages, partial success tracking)
v8.54.2 - Offline Mode Fix (opt-in offline mode, first-time install support)
v8.54.1 - UV Virtual Environment Support (installer compatibility fix)
v8.54.0 - Smart Auto-Capture System (intelligent pattern detection, 6 memory types, bilingual support)
v8.53.0 - Windows Service Management (Task Scheduler support, auto-startup, watchdog monitoring, 819 lines PowerShell automation)
v8.52.2 - Hybrid Backend Maintenance Enhancement (multi-PC association cleanup, drift prevention, Vectorize error handling)
v8.52.1 - Windows Embedding Fallback & Script Portability (DLL init failure fix, MCP_HTTP_PORT support)
v8.52.0 - Time-of-Day Emoji Icons (8 time-segment indicators, dark mode support, automatic timezone)
v8.51.0 - Graph Database Architecture (30x query performance, 97% storage reduction for associations)
v8.50.1 - Critical Bug Fixes (MCP_EMBEDDING_MODEL fix, installation script backend support, i18n quality analytics complete)
v8.50.0 - Fallback Quality Scoring (DeBERTa + MS-MARCO hybrid, technical content rescue, 20/20 tests passing)
v8.49.0 - DeBERTa Quality Classifier (absolute quality assessment, eliminates self-matching bias)
v8.48.4 - Cloudflare D1 Drift Detection Performance (10-100x faster queries, numeric comparison fix)
v8.48.3 - Code Execution Hook Fix - 75% token reduction now working (fixed time_filter parameter, Python warnings, venv detection)
v8.48.2 - HTTP Server Auto-Start & Time Parser Improvements (smart service management, "last N periods" support)
v8.48.1 - Critical Hotfix - Startup Failure Fix (redundant calendar import removed, immediate upgrade required)
v8.48.0 - CSV-Based Metadata Compression (78% size reduction, 100% sync success, metadata validation)
v8.47.1 - ONNX Quality Evaluation Bug Fixes (self-match fix, association pollution, sync queue overflow, realistic distribution)
v8.47.0 - Association-Based Quality Boost (connection-based enhancement, network effect leverage, metadata persistence)
v8.46.3 - Quality Score Persistence Fix (ONNX scores in hybrid backend, metadata normalization)
v8.46.2 - Session-Start Hook Crash Fix + Hook Installer Improvements (client-side tag filtering, isolated version metadata)
v8.46.1 - Windows Hooks Installer Fix + Quality System Integration (UTF-8 console configuration, backend quality scoring)
v8.45.3 - ONNX Ranker Model Export Fix (automatic model export, offline mode support, 7-16ms CPU performance)
v8.45.2 - Dashboard Dark Mode Consistency Fixes (global CSS overrides, Chart.js dark mode support)
v8.45.1 - Quality System Test Infrastructure Fixes (HTTP API router, storage retrieval, async test client)
v8.45.0 - Memory Quality System - AI-Driven Automatic Quality Scoring (ONNX-powered local SLM, multi-tier fallback, quality-based retention)
v8.44.0 - Multi-Language Expansion (Japanese, Korean, German, French, Spanish - 359 keys each, complete i18n coverage)
v8.43.0 - Internationalization & Quality Automation (English/Chinese i18n, Claude branch automation, quality gates)
v8.42.1 - MCP Resource Handler Fix (AttributeError with Pydantic AnyUrl objects)
v8.42.0 - Memory Awareness Enhancements (visible memory injection, quality session summaries, LLM-powered summarization)
v8.41.2 - Hook Installer Utility File Deployment (ALL 14 utilities copied, future-proof glob pattern)
v8.41.1 - Context Formatter Memory Sorting (recency sorting within categories, newest first)
v8.41.0 - Session Start Hook Reliability Improvements (error suppression, clean output, memory filtering, classification fixes)
v8.40.0 - Session Start Version Display (automatic version comparison, PyPI status labels)
v8.39.1 - Dashboard Analytics Bug Fixes: Three critical fixes (top tags filtering, recent activity display, storage report fields)
v8.39.0 - Performance Optimization: Storage-layer date-range filtering (10x faster analytics, 97% data transfer reduction)
v8.38.1 - Critical Hotfix: HTTP MCP JSON-RPC 2.0 compliance fix (Claude Code/Desktop connection failures resolved)
v8.38.0 - Code Quality: Phase 2b COMPLETE (~176-186 lines duplicate code eliminated, 10 consolidations)
v8.37.0 - Code Quality: Phase 2a COMPLETE (5 duplicate high-complexity functions eliminated)
v8.36.1 - Critical Hotfix: HTTP server startup crash fix (forward reference error in analytics.py)
v8.36.0 - Code Quality: Phase 2 COMPLETE (100% of target achieved, -39 complexity points)
v8.35.0 - Code Quality: Phase 2 Batch 1 (install.py, cloudflare.py, -15 complexity points)
v8.34.0 - Code Quality: Phase 2 Complexity Reduction (analytics.py refactored, 11 → 6-7 complexity)
v8.33.0 - Critical Installation Bug Fix + Code Quality Improvements (dead code cleanup, automatic MCP setup)
v8.32.0 - Code Quality Excellence: pyscn Static Analysis Integration (multi-layer QA workflow)
v8.31.0 - Revolutionary Batch Update Performance (21,428x faster memory consolidation)
v8.30.0 - Analytics Intelligence: Adaptive Charts & Critical Data Fixes (accurate trend visualization)
v8.28.1 - Critical HTTP MCP Transport JSON-RPC 2.0 Compliance Fix (Claude Code compatibility)
v8.28.0 - Cloudflare AND/OR Tag Filtering (unified search API, 3-5x faster hybrid sync)
v8.27.1 - Critical Hotfix: Timestamp Regression (created_at preservation during metadata sync)
v8.26.0 - Revolutionary MCP Performance (534,628x faster tools, 90%+ cache hit rate)
v8.25.0 - Hybrid Backend Drift Detection (automatic metadata sync, bidirectional awareness)
v8.24.4 - Code Quality Improvements from Gemini Code Assist (regex sanitization, DOM caching)
v8.24.3 - Test Coverage & Release Agent Improvements (tag+time filtering tests, version history fix)
v8.24.2 - CI/CD Workflow Fixes (bash errexit handling, exit code capture)
v8.24.1 - Test Infrastructure Improvements (27 test failures resolved, 63% → 71% pass rate)
v8.24.0 - PyPI Publishing Enabled (automated package publishing via GitHub Actions)
v8.23.1 - Stale Virtual Environment Prevention System (6-layer developer protection)
v8.23.0 - Consolidation Scheduler via Code Execution API (88% token reduction)

📖 Full Details: CHANGELOG.md | All Releases

Migration to v9.0.0

⚡ TL;DR: No manual migration needed - upgrades happen automatically!

Breaking Changes:

Memory Type Ontology: Legacy types auto-migrate to new taxonomy (task→observation, note→observation)
Asymmetric Relationships: Directed edges only (no longer bidirectional)

Migration Process:

Stop your MCP server
Update to latest version (git pull or pip install --upgrade mcp-memory-service)
Restart server - automatic migrations run on startup:
- Database schema migrations (009, 010)
- Memory type soft-validation (legacy types → observation)
- No tag migration needed (backward compatible)

Safety: Migrations are idempotent and safe to re-run

Breaking Changes

1. Memory Type Ontology

What Changed:

Legacy memory types (task, note, standard) are deprecated
New formal taxonomy: 5 base types (observation, decision, learning, error, pattern) with 21 subtypes
Type validation now defaults to 'observation' for invalid types (soft validation)

Migration Process: ✅ Automatic - No manual action required!

When you restart the server with v9.0.0:

Invalid memory types are automatically soft-validated to 'observation'
Database schema updates run automatically
Existing memories continue to work without modification

New Memory Types:

observation: General observations, facts, and discoveries
decision: Decisions and planning
learning: Learnings and insights
error: Errors and failures
pattern: Patterns and trends

Backward Compatibility:

Existing memories will be auto-migrated (task→observation, note→observation, standard→observation)
Invalid types default to 'observation' (no errors thrown)

2. Asymmetric Relationships

What Changed:

Asymmetric relationships (causes, fixes, supports, follows) now store only directed edges
Symmetric relationships (related, contradicts) continue storing bidirectional edges
Database migration (010) removes incorrect reverse edges

Migration Required: No action needed - database migration runs automatically on startup.

Code Changes Required: If your code expects bidirectional storage for asymmetric relationships:

# OLD (will no longer work):
# Asymmetric relationships were stored bidirectionally
result = storage.find_connected(memory_id, relationship_type="causes")

# NEW (correct approach):
# Use direction parameter for asymmetric relationships
result = storage.find_connected(
    memory_id,
    relationship_type="causes",
    direction="both"  # Explicit direction required for asymmetric types
)

Relationship Types:

Asymmetric: causes, fixes, supports, follows (A→B ≠ B→A)
Symmetric: related, contradicts (A↔B)

Performance Improvements

ontology validation: 97.5x faster (module-level caching)
Type lookups: 35.9x faster (cached reverse maps)
Tag validation: 47.3% faster (eliminated double parsing)

Testing

829/914 tests passing (90.7%)
80 new ontology tests with 100% backward compatibility
All API/HTTP integration tests passing

Support

If you encounter issues during migration:

Check Troubleshooting Guide
Review CHANGELOG.md for detailed changes
Open an issue: https://github.com/doobidoo/mcp-memory-service/issues

📚 Documentation & Resources

Installation Guide – Detailed setup instructions
Configuration Guide – Backend options and customization
Architecture Overview – How it works under the hood
Team Setup Guide – OAuth and cloud collaboration
Knowledge Graph Dashboard 🆕 – Interactive graph visualization guide
Troubleshooting – Common issues and solutions
API Reference – Programmatic usage
Wiki – Complete documentation
– AI-powered documentation assistant

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Quick Development Setup:

git clone https://github.com/doobidoo/mcp-memory-service.git
cd mcp-memory-service
pip install -e .  # Editable install
pytest tests/      # Run test suite

⭐ Support

If this saves you time, give us a star! ⭐

Issues: GitHub Issues
Discussions: GitHub Discussions
Wiki: Documentation Wiki

📄 License

Apache 2.0 – See LICENSE for details.

Never explain your project to AI twice.
Start using MCP Memory Service today.

⚠️ v6.17.0+ Script Migration Notice

Updating from an older version? Scripts have been reorganized for better maintainability:

Recommended: Use python -m mcp_memory_service.server in your Claude Desktop config (no path dependencies!)
Alternative 1: Use uv run memory server with UV tooling
Alternative 2: Update path from scripts/run_memory_server.py to scripts/server/run_memory_server.py
Backward compatible: Old path still works with a migration notice

⚠️ First-Time Setup Expectations

On your first run, you'll see some warnings that are completely normal:

"WARNING: Failed to load from cache: No snapshots directory" - The service is checking for cached models (first-time setup)
"WARNING: Using TRANSFORMERS_CACHE is deprecated" - Informational warning, doesn't affect functionality
Model download in progress - The service automatically downloads a ~25MB embedding model (takes 1-2 minutes)

These warnings disappear after the first successful run. The service is working correctly! For details, see our First-Time Setup Guide.

🐍 Python 3.13 Compatibility Note

sqlite-vec may not have pre-built wheels for Python 3.13 yet. If installation fails:

The installer will automatically try multiple installation methods
Consider using Python 3.12 for the smoothest experience: brew install python@3.12
Alternative: Use Cloudflare backend with --storage-backend cloudflare
See Troubleshooting Guide for details

🍎 macOS SQLite Extension Support

macOS users may encounter enable_load_extension errors with sqlite-vec:

System Python on macOS lacks SQLite extension support by default
Solution: Use Homebrew Python: brew install python && rehash
Alternative: Use pyenv: PYTHON_CONFIGURE_OPTS='--enable-loadable-sqlite-extensions' pyenv install 3.12.0
Fallback: Use Cloudflare or Hybrid backend: --storage-backend cloudflare or --storage-backend hybrid
See Troubleshooting Guide for details

🎯 Memory Awareness in Action

Intelligent Context Injection - See how the memory service automatically surfaces relevant information at session start:

What you're seeing:

🧠 Automatic memory injection - 8 relevant memories found from 2,526 total
📂 Smart categorization - Recent Work, Current Problems, Additional Context
📊 Git-aware analysis - Recent commits and keywords automatically extracted
🎯 Relevance scoring - Top memories scored at 100% (today), 89% (8d ago), 84% (today)
⚡ Fast retrieval - SQLite-vec backend with 5ms read performance
🔄 Background sync - Hybrid backend syncing to Cloudflare

Result: Claude starts every session with full project context - no manual prompting needed.

📚 Complete Documentation

👉 Visit our comprehensive Wiki for detailed guides:

🧠 v7.1.3 Natural Memory Triggers (Latest)

Natural Memory Triggers v7.1.3 Guide - Intelligent automatic memory awareness
- ✅ 85%+ trigger accuracy with semantic pattern detection
- ✅ Multi-tier performance (50ms instant → 150ms fast → 500ms intensive)
- ✅ CLI management system for real-time configuration
- ✅ Git-aware context integration for enhanced relevance
- ✅ Zero-restart installation with dynamic hook loading

🆕 v7.0.0 OAuth & Team Collaboration

🔐 OAuth 2.1 Setup Guide - NEW! Complete OAuth 2.1 Dynamic Client Registration guide
🔗 Integration Guide - Claude Desktop, Claude Code HTTP transport, VS Code, and more
🛡️ Advanced Configuration - Updated! OAuth security, enterprise features

🧬 v8.23.0+ Memory Consolidation

📊 Memory Consolidation System Guide - NEW! Automated memory maintenance with real-world performance metrics
- ✅ Dream-inspired consolidation (decay scoring, association discovery, compression, archival)
- ✅ 24/7 automatic scheduling (daily/weekly/monthly via HTTP server)
- ✅ Token-efficient Code Execution API (90% token reduction vs MCP tools)
- ✅ Real-world performance data (4-6 min for 2,495 memories with hybrid backend)
- ✅ Three manual trigger methods (HTTP API, MCP tools, Python API)

🚀 Setup & Installation

📋 Installation Guide - Complete installation for all platforms and use cases
🖥️ Platform Setup Guide - Windows, macOS, and Linux optimizations
⚡ Performance Optimization - Speed up queries, optimize resources, scaling

🧠 Advanced Topics

👨‍💻 Development Reference - Claude Code hooks, API reference, debugging
🔧 Troubleshooting Guide - Updated! OAuth troubleshooting + common issues
❓ FAQ - Frequently asked questions
📝 Examples - Practical code examples and workflows

📂 Internal Documentation

📊 Repository Statistics - 10 months of development metrics, activity patterns, and insights
🏗️ Architecture Specs - Search enhancement specifications and design documents
👩‍💻 Development Docs - AI agent instructions, release checklist, refactoring notes
🚀 Deployment Guides - Docker, dual-service, and production deployment
📚 Additional Guides - Storage backends, migration, mDNS discovery

✨ Key Features

🏆 Production-Ready Reliability 🆕 v8.9.0

Hybrid Backend - Fast 5ms local SQLite + background Cloudflare sync (RECOMMENDED default)
- Zero user-facing latency for cloud operations
- Automatic multi-device synchronization
- Graceful offline operation
Zero Database Locks - Concurrent HTTP + MCP server access works flawlessly
- Auto-configured SQLite pragmas (busy_timeout=15000,cache_size=20000)
- WAL mode with proper multi-client coordination
- Tested: 5/5 concurrent writes succeeded with no errors
Auto-Configuration - Installer handles everything
- SQLite pragmas for concurrent access
- Cloudflare credentials with connection testing
- Claude Desktop integration with hybrid backend
- Graceful fallback to sqlite_vec if cloud setup fails

📄 Document Ingestion System v8.6.0

Interactive Web UI - Drag-and-drop document upload with real-time progress
Multiple Formats - PDF, TXT, MD, JSON with intelligent chunking
Document Viewer - Browse chunks, view metadata, search content
Smart Tagging - Automatic tagging with length validation (max 100 chars)
Optional semtools - Enhanced PDF/DOCX/PPTX parsing with LlamaParse
Security Hardened - Path traversal protection, XSS prevention, input validation
7 New Endpoints - Complete REST API for document management

🔐 Enterprise Authentication & Team Collaboration

OAuth 2.1 Dynamic Client Registration - RFC 7591 & RFC 8414 compliant
Claude Code HTTP Transport - Zero-configuration team collaboration
JWT Authentication - Enterprise-grade security with scope validation
Auto-Discovery Endpoints - Seamless client registration and authorization
Multi-Auth Support - OAuth + API keys + optional anonymous access

🧠 Intelligent Memory Management

Semantic search with vector embeddings
Natural language time queries ("yesterday", "last week")
Tag-based organization with smart categorization
Memory consolidation with dream-inspired algorithms
Document-aware search - Query across uploaded documents and manual memories

🧬 Memory Type Ontology 🆕 v9.0.0

Formal Taxonomy - 5 base types with 21 specialized subtypes
- observation - General observations, facts, discoveries
- decision - Decisions, planning, architecture choices
- learning - Learnings, insights, patterns discovered
- error - Errors, failures, debugging information
- pattern - Patterns, trends, recurring behaviors
97.5x Performance - Module-level caching for validation
Auto-Migration - Backward compatible conversion from legacy types
Soft Validation - Warns but doesn't reject unknown types

📖 See Memory Type Ontology Guide for full taxonomy.

🔗 Knowledge Graph & Typed Relationships 🆕 v9.0.0

Relationship Types - Build semantic networks between memories
- Asymmetric: causes, fixes, supports, opposes, follows
- Symmetric: related, contradicts
Graph Operations - Query and traverse memory networks
- find_connected_memories - BFS traversal (1-2 hops)
- find_shortest_path - Compute paths between memories
- get_memory_subgraph - Extract subgraph for visualization
Semantic Reasoning - Automatic causal chain analysis and contradiction detection
Performance - 5-25ms queries, 30x faster than table scans

🧬 Knowledge Graph Dashboard 🆕 v9.2.0

Visualize your memory relationships with an interactive force-directed graph powered by D3.js v7.9.0.

Features:

Interactive Graph: Zoom, pan, drag nodes, hover for details
6 Typed Relationships: causes, fixes, contradicts, supports, follows, related
Relationship Chart: Bar chart showing distribution of relationship types
Multi-Language Support: Fully localized in 7 languages (en, zh, de, es, fr, ja, ko)
Dark Mode: Seamless theme integration with dashboard
Performance: Handles thousands of relationships smoothly (tested with 2,730 relationships)

Access: Navigate to Analytics → Knowledge Graph in the dashboard at http://localhost:8000

Key Capabilities:

Visual Exploration: Discover hidden connections between memories
Semantic Networks: See causal chains, fix relationships, and contradictions
Memory Types: Color-coded nodes by memory type (observation, decision, learning, error)
Real-time Updates: Graph automatically updates as you add new relationships

📖 See Knowledge Graph Dashboard Guide for complete documentation.

🔗 Universal Compatibility

Claude Desktop - Native MCP integration
Claude Code - HTTP transport + Memory-aware development with hooks
- 🪟 Windows Support: /session-start command for manual session initialization (workaround for issue #160)
- 🍎 macOS/Linux: Full automatic SessionStart hooks + slash command
VS Code, Cursor, Continue - IDE extensions
13+ AI applications - REST API compatibility

💾 Flexible Storage

Hybrid 🌟 (RECOMMENDED) - Fast local SQLite + background Cloudflare sync (v8.9.0 default)
- 5ms local reads with zero user-facing latency
- Multi-device synchronization
- Zero database locks with auto-configured pragmas
- Automatic backups and cloud persistence
SQLite-vec - Local-only storage (lightweight ONNX embeddings, 5ms reads)
- Good for single-user offline use
- No cloud dependencies
Cloudflare - Cloud-only storage (global edge distribution with D1 + Vectorize)
- Network-dependent performance

Note: All heavy ML dependencies (PyTorch, sentence-transformers) are now optional to dramatically reduce build times and image sizes. SQLite-vec uses lightweight ONNX embeddings by default. Install with --with-ml for full ML capabilities.

🪶 Lite Distribution 🆕 v8.76.0

For resource-constrained environments (CI/CD, edge devices):

pip install mcp-memory-service-lite

Benefits:

90% size reduction: 7.7GB → 805MB
ONNX-only: No transformers dependency
Same performance: Identical quality scoring
Ideal for: CI/CD pipelines, Docker images, embedded systems

Trade-offs:

Local-only quality scoring (no Groq/Gemini fallback)
ONNX embeddings only (no PyTorch)

🚀 Production Ready

Cross-platform - Windows, macOS, Linux
Service installation - Auto-start background operation
HTTPS/SSL - Secure connections with OAuth 2.1
Docker support - Easy deployment with team collaboration
Interactive Dashboard - Web UI at http://127.0.0.1:8000/ for complete management

💡 Basic Usage

📄 Document Ingestion (v8.6.0+)

# Start HTTP dashboard server (separate from MCP server)
uv run python scripts/server/run_http_server.py

# Access interactive dashboard
open http://127.0.0.1:8000/

# Upload documents via CLI
curl -X POST http://127.0.0.1:8000/api/documents/upload \
  -F "file=@document.pdf" \
  -F "tags=documentation,reference"

# Search document content
curl -X POST http://127.0.0.1:8000/api/search \
  -H "Content-Type: application/json" \
  -d '{"query": "authentication flow", "limit": 10}'

🔗 Team Collaboration with OAuth (v7.0.0+)

# Start OAuth-enabled HTTP server for team collaboration
export MCP_OAUTH_ENABLED=true
uv run python scripts/server/run_http_server.py

# Claude Code team members connect via HTTP transport
claude mcp add --transport http memory-service http://your-server:8000/mcp
# → Automatic OAuth discovery, registration, and authentication

🧠 Memory Operations

# Store a memory
uv run memory store "Fixed race condition in authentication by adding mutex locks"

# Search for relevant memories
uv run memory recall "authentication race condition"

# Search by tags
uv run memory search --tags python debugging

# Check system health (shows OAuth status)
uv run memory health

🔧 Configuration

Claude Desktop Integration

Recommended approach - Add to your Claude Desktop config (~/.claude/config.json):

{
  "mcpServers": {
    "memory": {
      "command": "python",
      "args": ["-m", "mcp_memory_service.server"],
      "env": {
        "MCP_MEMORY_STORAGE_BACKEND": "sqlite_vec"
      }
    }
  }
}

Alternative approaches:

// Option 1: UV tooling (if using UV)
{
  "mcpServers": {
    "memory": {
      "command": "uv",
      "args": ["--directory", "/path/to/mcp-memory-service", "run", "memory", "server"],
      "env": {
        "MCP_MEMORY_STORAGE_BACKEND": "sqlite_vec"
      }
    }
  }
}

// Option 2: Direct script path (v6.17.0+)
{
  "mcpServers": {
    "memory": {
      "command": "python",
      "args": ["/path/to/mcp-memory-service/scripts/server/run_memory_server.py"],
      "env": {
        "MCP_MEMORY_STORAGE_BACKEND": "sqlite_vec"
      }
    }
  }
}

Environment Variables

Hybrid Backend (v8.9.0+ RECOMMENDED):

# Hybrid backend with auto-configured pragmas
export MCP_MEMORY_STORAGE_BACKEND=hybrid
export MCP_MEMORY_SQLITE_PRAGMAS="busy_timeout=15000,cache_size=20000"

# Cloudflare credentials (required for hybrid)
export CLOUDFLARE_API_TOKEN="your-token"
export CLOUDFLARE_ACCOUNT_ID="your-account"
export CLOUDFLARE_D1_DATABASE_ID="your-db-id"
export CLOUDFLARE_VECTORIZE_INDEX="mcp-memory-index"

# Enable HTTP API
export MCP_HTTP_ENABLED=true
export MCP_HTTP_PORT=8000

# Security
export MCP_API_KEY="your-secure-key"

SQLite-vec Only (Local):

# Local-only storage
export MCP_MEMORY_STORAGE_BACKEND=sqlite_vec
export MCP_MEMORY_SQLITE_PRAGMAS="busy_timeout=15000,cache_size=20000"

Response Size Management 🆕 v9.0.0

Control maximum response size to prevent context overflow:

# Limit response size (recommended: 30000-50000)
export MCP_MAX_RESPONSE_CHARS=50000  # Default: unlimited

Applies to all retrieval tools:

retrieve_memory, recall_memory, retrieve_with_quality_boost
search_by_tag, recall_by_timeframe

Behavior:

Truncates at memory boundaries (preserves data integrity)
Recommended: 30000-50000 characters for optimal context usage

🏗️ Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   AI Clients    │    │  MCP Memory     │    │ Storage Backend │
│                 │    │  Service v8.9   │    │                 │
│ • Claude Desktop│◄──►│ • MCP Protocol  │◄──►│ • Hybrid 🌟     │
│ • Claude Code   │    │ • HTTP Transport│    │   (5ms local +  │
│   (HTTP/OAuth)  │    │ • OAuth 2.1 Auth│    │    cloud sync)  │
│ • VS Code       │    │ • Memory Store  │    │ • SQLite-vec    │
│ • Cursor        │    │ • Semantic      │    │ • Cloudflare    │
│ • 13+ AI Apps   │    │   Search        │    │                 │
│ • Web Dashboard │    │ • Doc Ingestion │    │ Zero DB Locks ✅│
│   (Port 8000)   │    │ • Zero DB Locks │    │ Auto-Config ✅  │
└─────────────────┘    └─────────────────┘    └─────────────────┘

🛠️ Development

Project Structure

mcp-memory-service/
├── src/mcp_memory_service/    # Core application
│   ├── models/                # Data models
│   ├── storage/               # Storage backends
│   ├── web/                   # HTTP API & dashboard
│   └── server.py              # MCP server
├── scripts/                   # Utilities & installation
├── tests/                     # Test suite
└── tools/docker/              # Docker configuration

Contributing

Fork the repository
Create a feature branch
Make your changes with tests
Submit a pull request

See CONTRIBUTING.md for detailed guidelines.

🆘 Support

📖 Documentation: Wiki - Comprehensive guides
🐛 Bug Reports: GitHub Issues
💬 Discussions: GitHub Discussions
🔧 Troubleshooting: Troubleshooting Guide
✅ Configuration Validator: Run python scripts/validation/validate_configuration_complete.py to check your setup
🔄 Backend Sync Tools: See scripts/README.md for Cloudflare↔SQLite sync

📊 In Production

Real-world metrics from active deployments:

1700+ memories stored and actively used across teams
5ms local reads with hybrid backend (v8.9.0)
Zero database locks with concurrent HTTP + MCP access (v8.9.0)
- Tested: 5/5 concurrent writes succeeded
- Auto-configured pragmas prevent lock errors
<500ms response time for semantic search (local & HTTP transport)
65% token reduction in Claude Code sessions with OAuth collaboration
96.7% faster context setup (15min → 30sec)
100% knowledge retention across sessions and team members
Zero-configuration setup success rate: 98.5% (OAuth + hybrid backend)

🏆 Recognition

Verified MCP Server
Featured AI Tool
Production-tested across 13+ AI applications
Community-driven with real-world feedback and improvements

📄 License

Apache License 2.0 - see LICENSE for details.

Ready to supercharge your AI workflow? 🚀

👉 Start with our Installation Guide or explore the Wiki for comprehensive documentation.

Transform your AI conversations into persistent, searchable knowledge that grows with you.

Memory Maintenance & Cleanup

Quick Reference

Task	Method	Time	Notes
Retag single memory	Dashboard UI	30s	Click memory → Edit → Save
Retag 10+ memories	Dashboard bulk	5m	Edit each individually
Retag 100+ memories	`retag_valuable_memories.py`	2m	Automatic, semantic tagging
Delete test data	`delete_test_memories.py`	1m	Bulk deletion with confirmation

Workflow: Clean Up Untagged Memories

After experiencing sync issues (like hybrid Cloudflare race conditions), untagged memories may accumulate:

# 1. Start dashboard
./start_all_servers.sh

# 2. Retag valuable memories automatically
python3 retag_valuable_memories.py
# → 340+ memories retagged
# → 0 failures

# 3. Delete remaining test data
python3 delete_test_memories.py
# → 209 test memories deleted
# → Database reduced from 5359 → 5150 memories

Dashboard Memory Edit

Open http://127.0.0.1:8000

To edit a single memory:

Find memory (search or filter)
Click to view details
Click "Edit Memory"
Modify tags (comma-separated)
Click "Update Memory"

Example:

Before: "needs-categorization"
After:  "release, v8.64, bug-fix, sync"

Automatic Tag Suggestions

The retag_valuable_memories.py script uses intelligent pattern matching:

Keywords detected:

Versions: release, v8, v1
Technologies: api, cloudflare, sync
Document types: documentation, setup-guide, tutorial
Projects: shodh, secondbrain, mcp-memory-service
Status: important, needs-categorization

Content analysis:

Content > 500 chars → important
Recognizes: release notes, API docs, setup guides, session summaries

Preventing Future Cleanup Issues

Version 8.64.0+:

✅ Soft-delete with tombstone support (v8.64.0)
✅ Bidirectional sync race condition fix (v8.64.0)
✅ Cloudflare hybrid sync validation (v8.64.1)

Best practices:

Use meaningful tags from the start
Review untagged memories regularly
Run cleanup scripts after major changes
Verify tags in Dashboard before deletion

Name		Name	Last commit message	Last commit date
Latest commit History 1,906 Commits
.claude		.claude
.github		.github
.pyscn		.pyscn
archive		archive
claude-hooks		claude-hooks
claude_commands		claude_commands
docs		docs
examples		examples
scripts		scripts
src/mcp_memory_service		src/mcp_memory_service
tests		tests
tools		tools
.commit-message		.commit-message
.coveragerc		.coveragerc
.dockerignore		.dockerignore
.env.example		.env.example
.gitattributes		.gitattributes
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
NOTICE		NOTICE
README.md		README.md
SECURITY.md		SECURITY.md
SPONSORS.md		SPONSORS.md
TEST_VALIDATION_REPORT.md		TEST_VALIDATION_REPORT.md
pyproject-lite.toml		pyproject-lite.toml
pyproject.toml		pyproject.toml
pytest.ini		pytest.ini
run_server.py		run_server.py
uv.lock		uv.lock

Uh oh!

License

doobidoo/mcp-memory-service

Folders and files

Latest commit

History

Repository files navigation

MCP Memory Service

Stop Re-Explaining Your Project to AI Every Session

⚡ Works With Your Favorite AI Tools

🖥️ CLI & Terminal AI

🎨 Desktop & IDE

🚀 Get Started in 60 Seconds

💡 Why You Need This

The Problem

The Solution

🌐 SHODH Ecosystem Compatibility

Compatible Implementations

Unified Schema Support

✨ Quick Start Features

🖥️ Dashboard Preview (v9.3.0)

🆕 Latest Release: v10.1.0 (January 25, 2026)

Migration to v9.0.0

Breaking Changes

1. Memory Type Ontology

2. Asymmetric Relationships

Performance Improvements

Testing

Support

📚 Documentation & Resources

🤝 Contributing

⭐ Support

📄 License

⚠️ v6.17.0+ Script Migration Notice

⚠️ First-Time Setup Expectations

🐍 Python 3.13 Compatibility Note

🍎 macOS SQLite Extension Support

🎯 Memory Awareness in Action

📚 Complete Documentation

🧠 v7.1.3 Natural Memory Triggers (Latest)

🆕 v7.0.0 OAuth & Team Collaboration

🧬 v8.23.0+ Memory Consolidation

🚀 Setup & Installation

🧠 Advanced Topics

📂 Internal Documentation

✨ Key Features

🏆 Production-Ready Reliability 🆕 v8.9.0

📄 Document Ingestion System v8.6.0

🔐 Enterprise Authentication & Team Collaboration

🧠 Intelligent Memory Management

🧬 Memory Type Ontology 🆕 v9.0.0

🔗 Knowledge Graph & Typed Relationships 🆕 v9.0.0

🧬 Knowledge Graph Dashboard 🆕 v9.2.0

🔗 Universal Compatibility

💾 Flexible Storage

🪶 Lite Distribution 🆕 v8.76.0

🚀 Production Ready

💡 Basic Usage

📄 Document Ingestion (v8.6.0+)

🔗 Team Collaboration with OAuth (v7.0.0+)

🧠 Memory Operations

🔧 Configuration

Claude Desktop Integration

Environment Variables

Response Size Management 🆕 v9.0.0

🏗️ Architecture

🛠️ Development

Project Structure

Contributing

🆘 Support

📊 In Production

🏆 Recognition

📄 License

Transform your AI conversations into persistent, searchable knowledge that grows with you.

Memory Maintenance & Cleanup

Quick Reference

Workflow: Clean Up Untagged Memories

Dashboard Memory Edit

Automatic Tag Suggestions

Preventing Future Cleanup Issues

Packages