AgentIndex icon
AgentIndex
mcp-local-memory logo
mcp-local-memory
★ 60
vs
engram-memory logo
engram-memory
★ 38

mcp-local-memory vs engram-memory

mcp-local-memory: mcp-local-memory is a local-first MCP server designed to provide AI agents with shared, durable memory without relying on Docker or cloud services. It achieves this through a powerful combination of hybrid semantic search, SQLite FTS5, and a structured knowledge graph, supporting features like temporal recall and adaptive ranking.; 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-local-memory logo
mcp-local-memoryMemory & Context · ★ 60

Provide persistent and shared memory for AI agents in local environments.

Read mcp-local-memory full review →
engram-memory logo
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.

Read engram-memory full review →
02

Side-by-Side Comparison

Field
mcp-local-memory logomcp-local-memory
engram-memory logoengram-memory
Category
Memory & Context
Memory & Context
Stars
★ 60
★ 38
License
MIT
NOASSERTION
Install Command
npm install -g @beledarian/mcp-local-memory@2
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
1mo ago
4mo ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
AI Agents, Memory Management, Knowledge Graph
AI Agent Memory, Self-hosted, Vector Database
03

Features

mcp-local-memory logomcp-local-memory
01Shared memory across multiple AI agents
02Hybrid semantic and keyword recall
03Structured knowledge graph for context management
04Temporal memory recall with natural language dates
05Adaptive memory ranking based on multiple factors
engram-memory logoengram-memory
01Three-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-local-memory logomcp-local-memory
↳Provide persistent and shared memory for AI agents in local environments.
↳Build knowledge bases and manage context for complex AI applications.
↳Facilitate local-first AI agent development and testing without external dependencies.
↳Serve as a centralized memory server for distributed AI agent systems via HTTP/SSE.
engram-memory logoengram-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.
FAQ

FAQ

What is the difference between mcp-local-memory and engram-memory?
Both mcp-local-memory and engram-memory are in the Memory & Context category. mcp-local-memory has 60 stars, while engram-memory has 38 stars.
Which is better, mcp-local-memory or engram-memory?
The best choice depends on your use case. Choose mcp-local-memory if Provide persistent and shared memory for AI agents in local environments., 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-local-memory free or open source?
Yes, mcp-local-memory is open source on GitHub (MIT).
Is engram-memory free or open source?
Yes, engram-memory is open source on GitHub (NOASSERTION).
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Related

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