context-mode

★ 31.8k

engrim

★ 299

context-mode vs engrim

Q: Which is better, context-mode or engrim?

By GitHub stars, context-mode has more community adoption, but the best choice depends on your specific use case.

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.; engrim: Engrim is a universal, local-first SQLite memory engine specifically engineered for autonomous AI coding agents, designed to solve the '200,000-token context window trap'. It provides high-precision, curated episodic working memory, allowing developers to switch between various models and environments on the same codebase without losing architectural decisions or project state.

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.

Read context-mode full review →

engrimMemory & Context · ★ 299

Maintaining Project Context Across Agent Sessions: Developers can use Engrim to prevent LLMs from losing architectural decisions, user constraints, or project state when chat sessions are cleared or models are switched.

Read engrim full review →

Side-by-Side Comparison

Field

context-mode

engrim

Features

context-mode

01Context 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.

engrim

01Precision Working Memory: Replaces raw transcript replay with ~4,000 characters of high-precision, curated episodic memory, injected at boot with zero attention dilution.

02Cross-Model/Agent Compatibility: Provides a universal substrate for memory, allowing decisions made in one agent (e.g., Claude Code) to be visible and usable in others (e.g., Antigravity, Cursor).

03Local-First & Private Storage: Stores all memories locally in a SQLite file (~/.engrim/memory.db) with WAL mode and POSIX 0600 permissions, ensuring 100% privacy with no cloud sync or telemetry.

04Self-Healing Diagnostics: The `engrim doctor --fix` command verifies all hooks and installs portable PATH fallbacks, ensuring reliable operation across machines and OSes without silent failures.

05Hybrid Retrieval & Minder: Employs a hybrid lexical (BM25) and vector (model2vec) search for efficient and relevant memory recall in approximately 30ms.

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

engrim

↳Maintaining Project Context Across Agent Sessions: Developers can use Engrim to prevent LLMs from losing architectural decisions, user constraints, or project state when chat sessions are cleared or models are switched.

↳Collaborative Multi-Agent Development: Enabling multiple AI coding agents (e.g., Antigravity, Claude Code, Cursor) to work on the same codebase and share a consistent, evolving memory store.

↳Continue-As-Clear Workflow: Allows users to clear their agent's context window at any time, with Engrim automatically re-injecting the active memory pack for seamless continuation without memory loss.

↳Auditing Agent Provenance: Tracking which agent made specific architectural decisions or added facts to the project's memory, enhancing transparency in multi-agent environments.

Best For

context-mode

Most PopularTrending

engrim

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FAQ

What is the difference between context-mode and engrim?

Both context-mode and engrim are in the Memory & Context category. context-mode has 31.8k stars, while engrim has 299 stars.

Which is better, context-mode or engrim?

The best choice depends on your use case. Choose context-mode if Deep repository research and analysis (e.g., architecture, contributors, issues), and engrim if Maintaining Project Context Across Agent Sessions: Developers can use Engrim to prevent LLMs from losing architectural decisions, user constraints, or project state when chat sessions are cleared or models are switched..

Is context-mode free or open source?

Yes, context-mode is open source on GitHub (Elastic License 2.0).

Is engrim free or open source?

Yes, engrim is open source on GitHub (MIT).

Cloud Infrastructure

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Alternatives to context-mode →Alternatives to engrim →context-mode details →engrim details →context-mode vs headroom →Trail-Code vs context-mode →

TL;DR

Side-by-Side Comparison

Features

Use Cases

Best For

FAQ

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