context-mode
★ 31.8k
vs
mnemo
★ 12
context-mode vs mnemo
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.; mnemo: Mnemo is an open, free, and unlimited persistent AI memory system featuring hybrid search and embedded synchronization. It integrates full-text search with vector search, temporal decay, and importance boosting for advanced retrieval.
01
TL;DR
context-modeMemory & Context · ★ 31.8k
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.
mnemoMemory & Context · ★ 12
Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making.
02
Side-by-Side Comparison
Field
context-modemnemoCategory
Memory & Context
Memory & Context
Stars
★ 31.8k
★ 12
License
Elastic License 2.0
Apache-2.0
Install Command
npm install -g context-mode
/plugin marketplace add n24q02m/claude-plugins && /plugin install mnemo-mcp@n24q02m-plugins
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
antigravity, claude, claude-code
AI Memory, Hybrid Search, Vector Database
03
Features
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.
mnemo01Hybrid retrieval combining full-text search (FTS5) and vector search, fused via Reciprocal Rank Fusion, then re-ranked with temporal decay and importance boost.
02Automatic entity extraction and relation tracking to build a temporal knowledge graph, boosting top search results by graph proximity.
03Multi-machine sync via Google Drive with JSONL-based merge sync, and end-to-end encrypted passport sync using AES-256-GCM and Argon2id for secure cross-device bootstrap.
04LLM-driven compression of older memories and LLM summarization of related memories for STM-to-LTM consolidation, achieving significant token reduction.
05Zero-config local setup using Fastretrieval's built-in Qwen3 ONNX embedding and reranking models, requiring no external API keys for basic operation.
04
Use Cases
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
mnemo↳Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making.
↳Building and querying a temporal knowledge graph to understand historical states and relationships of entities within an AI system's memory.
↳Synchronizing AI memory across multiple machines or devices securely, enabling a consistent knowledge base for agents.
↳Improving the efficiency of LLM interactions by compressing older memories and consolidating related information.
↳Integrating with various AI clients (e.g., Claude Code, Gemini CLI, Cursor) as an MCP server for advanced memory management.
05
Best For
context-modeMost PopularTrending
mnemo—
FAQ
FAQ
What is the difference between context-mode and mnemo?
Both context-mode and mnemo are in the Memory & Context category. context-mode has 31.8k stars, while mnemo has 12 stars.
Which is better, context-mode or mnemo?
The best choice depends on your use case. Choose context-mode if Deep repository research and analysis (e.g., architecture, contributors, issues), and mnemo if Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making..
Is context-mode free or open source?
Yes, context-mode is open source on GitHub (Elastic License 2.0).
Is mnemo free or open source?
Yes, mnemo is open source on GitHub (Apache-2.0).
Cloud Infrastructure
AdDeploy on DigitalOcean
Host your MCP servers, Docker containers, and AI agents with $200 free credit over 60 days.
→