engram-memory
★ 38
vs
context-mode
★ 31.7k
engram-memory vs context-mode
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.; context-mode: Every tool call in an MCP (Model-Controller-Program) environment dumps raw data into the context window, quickly consuming space and causing the agent to lose track of ongoing tasks. Context Mode is an MCP server that tackles this by sandboxing tool outputs to significantly reduce context usage, tracking session events in SQLite for continuity, and promoting 'think in code' to minimize data processing within the LLM.
01
TL;DR
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.
context-modeMemory & Context · ★ 31.7k
When to choose:
- Your sessions fill up with tool output such as Playwright snapshots, GitHub issue lists or logs.
- You want work state (edits, git operations, tasks, decisions) to survive context compaction without being dumped back into the window.
- You use a hook-capable agent, where tool routing happens automatically.
When to skip:
- You need an OSI open-source licence: it uses the Elastic License 2.0, which restricts uses such as offering it as a managed service.
- Your sessions are short and rarely hit the context limit.
- You do not want hooks changing how your agent's tools behave.
02
Side-by-Side Comparison
Field
engram-memorycontext-modeCategory
Memory & Context
Memory & Context
Stars
★ 38
★ 31.7k
License
NOASSERTION
Elastic License 2.0
Install Command
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
npm install -g context-mode
Updated
4mo ago
1d ago
Open Source
Yes
Yes
Tags
AI Agent Memory, Self-hosted, Vector Database
antigravity, claude, claude-code
03
Features
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.
context-mode01Context Saving: Sandbox tools keep raw data out of the context window, achieving up to 98% reduction.
02Session Continuity: Tracks every file edit, git operation, task, and user decision in SQLite for seamless session resume.
03Think in Code: Promotes LLMs to program analysis, not compute it, saving 100x context by logging only results.
04Batch Execution & Search: Run multiple commands/queries in one call with tools like `ctx_batch_execute`.
05Advanced Knowledge Base: Uses SQLite FTS5 with BM25 ranking, smart snippets, and TTL cache for efficient information retrieval.
04
Use Cases
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.
context-mode↳Deep repository research and analysis (e.g., architecture, contributors, issues)
↳Analyze Git history to identify top contributors, commit frequency, and most changed files
↳Efficiently process large JSON APIs, web pages, or logs without flooding the context window
05
Best For
engram-memory—
context-modeMost PopularTrending
FAQ
FAQ
What is the difference between engram-memory and context-mode?
Both engram-memory and context-mode are in the Memory & Context category. engram-memory has 38 stars, while context-mode has 31.7k stars.
Which is better, engram-memory or context-mode?
The best choice depends on your use case. Choose 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., and context-mode if Deep repository research and analysis (e.g., architecture, contributors, issues).
Is engram-memory free or open source?
Yes, engram-memory is open source on GitHub (NOASSERTION).
Is context-mode free or open source?
Yes, context-mode is open source on GitHub (Elastic License 2.0).
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