MCP-memento
★ 11
vs
cortex
★ 35
MCP-memento vs cortex
MCP-memento: Memento-mcp is a local-first MCP server designed to provide AI agents with durable, high-signal memory for code repositories. It offers indexed code context, semantic relationships, fast search capabilities, and explicit notes that persist across sessions.; cortex: Cortex is a private, free, and local memory engine for personal AI agents, built with Rust. It provides multi-tier, self-evolving long-term memory that persists across sessions and devices, offering sub-millisecond performance and end-to-end encrypted cloud synchronization.
01
TL;DR
MCP-mementoMemory & Context · ★ 11
Enhancing AI agent performance with rich, persistent code context.
cortexMemory & Context · ★ 35
Providing persistent, private long-term memory for AI agents and LLMs across conversation sessions.
02
Side-by-Side Comparison
Field
MCP-mementocortexCategory
Memory & Context
Memory & Context
Stars
★ 11
★ 35
License
MIT
MIT
Install Command
git clone https://github.com/caiowilson/MCP-memento.git && cd MCP-memento && make build
brew tap gambletan/tap && brew install cortex-mcp-server
Updated
1mo ago
6d ago
Open Source
Yes
Yes
Tags
AI Agent Memory, Code Indexing, Semantic Search
AI Agent Memory, Local Storage, Privacy-Preserving AI
03
Features
MCP-memento01Provides durable, high-signal memory for AI agents by indexing code context.
02Supports fast search and retrieval of code context based on semantic relationships.
03Stores explicit, repo-scoped notes that persist across sessions.
04Integrates with Claude Code and Claude Desktop as an MCP server.
05Offers a companion VS Code extension for installation and configuration.
cortex01Private by Default: Memories reside in a local SQLite file, ensuring zero telemetry and data privacy.
02Real, Multi-Tier Memory: Features 4 memory tiers (Working, Episodic, Semantic, Procedural), multi-signal retrieval, Bayesian beliefs, and a cross-channel people graph.
03Sub-millisecond Performance: Achieves 156µs ingest and 568µs search speeds, significantly faster than cloud memory APIs.
04Cross-Device End-to-End Encrypted Sync: Optionally syncs memories across devices through your own cloud storage (iCloud, Google Drive, etc.) with AES-256-GCM encryption.
05Drop-in Integration: Serves as an MCP server for Claude, offers Python bindings, and integrates with frameworks like LangGraph, DeerFlow, and OpenClaw.
04
Use Cases
MCP-memento↳Enhancing AI agent performance with rich, persistent code context.
↳Enabling AI-powered code search and understanding within a repository.
↳Managing and retrieving explicit notes or institutional knowledge related to specific codebases.
↳Integrating long-term memory capabilities into AI development workflows via MCP clients.
cortex↳Providing persistent, private long-term memory for AI agents and LLMs across conversation sessions.
↳Enabling AI assistants to remember user preferences, facts, and past interactions without sending data to external servers.
↳Building personal AI systems where user data stays entirely on-device or synced via user's own encrypted cloud storage.
↳Integrating advanced memory capabilities (e.g., people graph, Bayesian beliefs, contradiction detection) into agent orchestration platforms like LangGraph or DeerFlow.
↳Developing AI applications that require low-latency, real-time memory access and context generation for prompt injection.
FAQ
FAQ
What is the difference between MCP-memento and cortex?
Both MCP-memento and cortex are in the Memory & Context category. MCP-memento has 11 stars, while cortex has 35 stars.
Which is better, MCP-memento or cortex?
The best choice depends on your use case. Choose MCP-memento if Enhancing AI agent performance with rich, persistent code context., and cortex if Providing persistent, private long-term memory for AI agents and LLMs across conversation sessions..
Is MCP-memento free or open source?
Yes, MCP-memento is open source on GitHub (MIT).
Is cortex free or open source?
Yes, cortex is open source on GitHub (MIT).
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