context-mode vs hindsight
The two are close in size: 33.0k stars for context-mode, 56.8k for hindsight. Over the days we have tracked them context-mode moved +68.5% and hindsight +198.4%, so hindsight is growing faster right now.
They split the axes: context-mode leads on context depth, hindsight on model freedom and setup ease.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Sandboxes large tool outputs and persistently indexes session events (SQLite FTS5 + BM25) so agents retrieve only relevant fragments, drastically shrinking context usage while preserving continuity across many MCP clients.
- Stars
- 33.0k
- Tracked growth
- +68.5%
- Maturity
- ●●●●●
- Last commit
- 9m ago
- Language
- TypeScript
- License
- NOASSERTION
- Cost to run
- Free, local install
Hindsight provides a learning-focused agent memory with biomimetic data structures and a reflect operation to build mental models, going beyond simple RAG-style recall.
- Stars
- 56.8k
- Tracked growth
- +198.4%
- Maturity
- ●●●●●
- Last commit
- 7h ago
- Language
- Python
- License
- MIT
- Cost to run
- Your LLM API key (or self-hosted models); Hindsight itself can be self-hosted
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | context-mode | hindsight |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Whole-repo analysis | ●●●●● Related context |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● BM25 & sandboxing | ●●●●● Rerank & filtering |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Config files & hooks | ●●●●● Config API & metadata |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Fully local | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Multiple providers | ●●●●● Bring-your-own / local |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Config + one command | ●●●●● One-command start |
Which one to pick
Pick context-mode if…
Context-efficient — drastically reduces context bloat and preserves session continuity across IDEs and CLIs via local MCP hooks and searchable session storage.
- Context depth: Whole-repo analysis (5/5 against 3/5)
Pick hindsight if…
Learning-focused — choose Hindsight when you need agents that form and reflect on long-term memories (mental models) with easy self-hosted deployment and multi-provider model support.
- Model freedom: Bring-your-own / local (5/5 against 3/5)
- Setup ease: One-command start (5/5 against 3/5)
What people want from each one
vectorize-io/hindsight
Questions people ask
Is context-mode better than hindsight?
They split the axes: context-mode leads on context depth, hindsight on model freedom and setup ease. context-mode is worth picking when context-efficient — drastically reduces context bloat and preserves session continuity across IDEs and CLIs via local MCP hooks and searchable session storage.
Which of context-mode and hindsight keeps my code private?
context-mode: Fully local (5/5). hindsight: Self-hostable (4/5).
What does each one cost to run?
context-mode: Free, local install. hindsight: Your LLM API key (or self-hosted models); Hindsight itself can be self-hosted.
Full profiles: mksglu/context-mode and vectorize-io/hindsight. Everything else in Memory & context.