Memento Protocol Enhanced
An enhanced wrapper around memento-mcp that adds sophisticated memory management capabilities inspired by the original ChatGPT memory design concepts.
š Features
š Protocol Memory System
Rule Enforcement Outside LLM: Protocols are enforced deterministically, not subject to model forgetfulness
YAML Configuration: Easy-to-edit protocol definitions
Auto Git Backup: Automatic version control before file modifications
Extensible Actions: Git operations, file system actions, API calls
šÆ Quality Management
Two-Stage Filtering: Heuristic + LLM validation for accuracy
Confidence Scoring: Tracks reliability of memories
Freshness Decay: Automatic aging and archival of old memories
Archival Tiers: Hot/Warm/Cold storage based on usage and age
š Enhanced Search (Hybrid Recall)
Multiple Strategies: Semantic vector, keyword matching, temporal relevance, confidence weighting
Hybrid Scoring: Combines multiple search approaches for better results
Quality Filtering: Filters results by confidence and relevance thresholds
Search Metadata: Detailed information about search process and results
š "Ask the Scribe" Synthesis Reports
Memory Synthesis: Combines related memories into coherent summaries
Insight Extraction: Identifies key patterns and connections
Confidence Tracking: Rates the reliability of synthesized information
Query-Focused: Tailored responses to specific questions
š§ Wrapper Architecture
Preserves Compatibility: Works as a drop-in replacement for memento-mcp
Upstream Safe: Doesn't fork memento-mcp, wraps it instead
Optional Features: All enhancements can be enabled/disabled
Graceful Fallbacks: Falls back to basic functionality if enhancements fail
š Quick Start
Installation
Basic Usage
Run Example
š Protocol System
Protocols are defined in YAML files and enforce rules automatically:
šÆ Quality Management
The quality system addresses six failure modes identified in basic memory systems:
Noise Accumulation: Filters low-quality information
Confidence Erosion: Tracks reliability over time
Retrieval Brittleness: Multiple search strategies for robustness
Temporal Confusion: Time-aware relevance scoring
Context Loss: Preserves rich metadata and relationships
Scale Degradation: Efficient archival and tier management
š Search Strategies
The hybrid search system combines multiple approaches:
Semantic Vector: Embedding-based similarity search
Keyword Matching: Exact term matching with scoring
Temporal Relevance: Recent memories weighted higher
Confidence Weighted: High-confidence memories prioritized
š Synthesis Reports
"Ask the Scribe" generates comprehensive reports by:
Multi-Strategy Search: Finds relevant memories using all search approaches
Quality Filtering: Removes low-confidence or irrelevant results
Insight Extraction: Identifies patterns and key information
Coherent Synthesis: Combines findings into readable summaries
Confidence Rating: Provides reliability assessment
šļø Architecture
The wrapper is built in distinct layers:
š§ Configuration
š MCP Server
The package includes a complete MCP server implementation:
š ļø Development
Requirements
Node.js 18+
Git (for protocol auto-backup)
Scripts
Adding Protocols
Create YAML file in
protocols/
directoryDefine triggers, conditions, and actions
Protocol engine loads automatically
Extending Search
Add new search strategies in src/enhanced-search/index.js
:
š¤ Integration
With HexTrackr
This wrapper was designed for integration with HexTrackr but works standalone:
With Other Projects
The wrapper preserves full memento-mcp compatibility:
šÆ Original Vision
This implementation realizes the original ChatGPT memory design vision:
"Some of our improvements with how we handle the searching and the semantics might actually be an improvement" - User feedback
The wrapper addresses fundamental limitations in basic memory systems while maintaining simplicity and compatibility.
Failure Modes Addressed
LLM compliance is unreliable ā Protocol enforcement outside LLM
Noisy memories from keyword scraping ā Two-stage filtering
Memory bloat & drift ā Freshness decay + archival tiers
Conflicting protocols ā Priority and scope management
Identity & grounding issues ā Stable IDs and linkage
Security & PII sprawl ā Secret scrubbing and access controls
Core Innovations
Hybrid Recall: Symbolic (SQL-like) + Vector (semantic) + Raw transcripts
Protocol Memory: Rules enforced deterministically, not stored as "memories"
Quality Pipeline: Heuristics ā LLM validation ā Confidence scoring
Archival Strategy: Hot/warm/cold tiers based on adjusted confidence
š License
MIT License - see LICENSE file for details.
š Links
memento-mcp - Core memory functionality
HexTrackr - Integration target project
Model Context Protocol - MCP specification
Enhanced memory management that learns, improves, and remembers.
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
An enhanced memory management system that wraps memento-mcp with sophisticated features including protocol enforcement, quality scoring, hybrid search strategies, and synthesis reports. Enables intelligent memory storage, retrieval, and analysis with automatic archival and confidence tracking.
Related MCP Servers
- AsecurityAlicenseAqualityA custom Memory MCP Server that acts as a cache for Infrastructure-as-Code information, allowing users to store, summarize, and manage notes with a custom URI scheme and simple resource handling.Last updated -231MIT License
- AsecurityAlicenseAqualityA customized MCP memory server that enables creation and management of a knowledge graph with features like custom memory paths and timestamping for capturing interactions via language models.Last updated -104MIT License
- -securityFlicense-qualityAn MCP server that allows Claude and other LLMs to manage persistent memories across conversations through text file storage, enabling commands to add, search, delete and list memory entries.Last updated -207
- -securityAlicense-qualityEnhances the MCP memory server by implementing PouchDB for robust document storage and enabling the creation and management of a knowledge graph that captures interactions via language models.Last updated -4MIT License