mcp-memory-service
★ 2.0k
vs
engram-memory
★ 38
mcp-memory-service vs engram-memory
mcp-memory-service: MCP Memory Service prevents AI assistants from losing context across sessions by automatically capturing project architecture, decisions, and code patterns. This ensures your AI always remembers essential information, eliminating the need for repetitive re-explanation and saving valuable development time.; engram-memory: Engram Memory provides AI agents with persistent, self-hosted memory, eliminating session-end forgetfulness and API costs. It features a three-tiered recall engine for efficient storage, search, and retrieval of semantic embeddings on your own hardware.
01
TL;DR
mcp-memory-serviceMemory & Context · ★ 2.0k
When to choose:
- You use Claude Code, Claude Desktop, Cursor, VS Code or another MCP client and want chat sessions to stop starting from zero.
- You want a choice of storage: local SQLite, Cloudflare for multi-device sync, or a hybrid.
- You need team features: the README lists OAuth, a dashboard and document ingestion.
When to skip:
- Your problem is codebase navigation rather than conversation memory; a code-graph tool or a project scaffold fits better.
- You handle sensitive material and cannot put it in a persistent store, especially with cloud sync.
- You want a short README to start from: it mixes release notes with documentation.
engram-memoryMemory & Context · ★ 38
Providing long-term memory for AI agents (e.g., Claude Code, Cursor) to remember codebase details, user preferences, and architectural decisions across sessions.
02
Side-by-Side Comparison
Field
mcp-memory-serviceengram-memoryCategory
Memory & Context
Memory & Context
Stars
★ 2.0k
★ 38
License
Apache-2.0
NOASSERTION
Install Command
pip install mcp-memory-service
docker run -d --name engram-memory --restart unless-stopped -p 6333:6333 -p 11435:11435 -p 8585:8585 -v engram_data:/data engrammemory/engram-memory:latest
Updated
2d ago
4mo ago
Open Source
Yes
Yes
Tags
AI Memory, Context Management, Developer Tools
AI Agent Memory, Self-hosted, Vector Database
03
Features
mcp-memory-service01Persistent Memory
02Smart Retrieval
03Multi-Client Compatibility
04Cloud Sync (Optional)
05Web Dashboard
engram-memory01Three-tiered recall engine (Hot-Tier Cache, Multi-Head Hash Index, Hybrid Vector Search) for fast and efficient memory retrieval.
02Persistent memory management with semantic embedding (store, search, recall, forget, consolidate) for AI agents.
03Local-first operation with self-hosted components (Qdrant, FastEmbed, MCP server) for data privacy and zero API costs.
04Kuzu-backed entity graph for tracking entities, co-retrieval patterns, and spreading activation.
05Advanced memory capabilities including conflict detection, temporal queries, and an "answer from memory" function.
06Hive Memory for multi-device sharing, enabling shared memory pools across different agents and devices.
04
Use Cases
mcp-memory-service↳Maintaining AI context across multiple development sessions.
↳Avoiding repetitive explanations of project architecture and tech stack to AI.
↳Enhancing continuous and intelligent collaboration with AI assistants.
engram-memory↳Providing long-term memory for AI agents (e.g., Claude Code, Cursor) to remember codebase details, user preferences, and architectural decisions across sessions.
↳Enabling multi-agent systems to share a common knowledge base and collaborate effectively through shared memory pools (Hive Memory).
↳Answering complex questions by synthesizing information from an agent's stored memories, both locally and optionally with cloud enhancement.
↳Auditing an agent's knowledge at specific points in time or over date ranges using temporal queries for incident analysis or historical context.
↳Storing and retrieving user preferences, facts, decisions, goals, and insights efficiently and semantically for personalized agent interactions.
05
Best For
mcp-memory-serviceEssentialTrending
engram-memory—
FAQ
FAQ
What is the difference between mcp-memory-service and engram-memory?
Both mcp-memory-service and engram-memory are in the Memory & Context category. mcp-memory-service has 2.0k stars, while engram-memory has 38 stars.
Which is better, mcp-memory-service or engram-memory?
The best choice depends on your use case. Choose mcp-memory-service if Maintaining AI context across multiple development sessions., and engram-memory if Providing long-term memory for AI agents (e.g., Claude Code, Cursor) to remember codebase details, user preferences, and architectural decisions across sessions..
Is mcp-memory-service free or open source?
Yes, mcp-memory-service is open source on GitHub (Apache-2.0).
Is engram-memory free or open source?
Yes, engram-memory is open source on GitHub (NOASSERTION).
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