causal-memory
★ 101
vs
context-mode
★ 31.8k
causal-memory vs context-mode
causal-memory: Causal-memory is an agent memory system with a causal core, uniquely modeling both excitatory and inhibitory connections for robust long-term retention. It enables agents to understand not just what happened, but why it worked or failed, and anticipate outcomes, thereby preventing repeated mistakes.; 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
causal-memoryMemory & Context · ★ 101
Preventing Repeated Mistakes: Agents can recall past `decision → outcome` causal edges, avoiding re-fixing the same bug or repeating past failed architectural choices.
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.
02
Side-by-Side Comparison
Field
causal-memorycontext-modeCategory
Memory & Context
Memory & Context
Stars
★ 101
★ 31.8k
License
Apache-2.0
Elastic License 2.0
Install Command
git clone https://github.com/JingxuanC/causal-memory.git && cd causal-memory && cargo build --release
npm install -g context-mode
Updated
1w ago
1d ago
Open Source
Yes
Yes
Tags
Agent Memory, Causal Reasoning, Long-term Memory
antigravity, claude, claude-code
03
Features
causal-memory01Causal Core with Excitatory and Inhibitory Connections: Models 'caused', 'enabled', and 'prevented' relationships using typed causal semantics and negative activation spread (GABA analogue).
02Immutable Consolidation & Q-value Dynamics: Employs hippocampus-style SWR (Sleep-Wake Replay) consolidation with LTP/LTD/GC, Q-value dynamics, and novelty-entropy triggers for robust memory evolution.
03Intervention & Counterfactual Query: Enables forward simulation to predict outcomes before action and contrastive analysis to compare outcomes of different alternatives.
04Compaction Survival: Stores causal information in an external SQLite database, making it immune to context window compaction and preserving critical 'why' knowledge.
05Unified Memory Graph: Integrates facts, temporal state, and decision-outcome causal edges into a single graph, accessible via RRF-fused retrieval (BM25 + semantic).
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
causal-memory↳Preventing Repeated Mistakes: Agents can recall past `decision → outcome` causal edges, avoiding re-fixing the same bug or repeating past failed architectural choices.
↳Proactive Warning and Intervention: Before committing risky actions (e.g., `git push --no-verify`), the system can fire DANGER warnings based on recorded past negative outcomes.
↳Root Cause Analysis: Trace multi-hop backward causal chains to identify the ultimate root cause of failures or unexpected outcomes.
↳Informed Decision Making: Agents can perform counterfactual comparisons between alternative actions, leveraging known outcomes to choose the best path.
↳Cross-Task Lesson Transfer: Discover and apply meta-edges (e.g., `similar_to`, `repeated`) to transfer lessons and patterns across different tasks or sessions.
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
causal-memory—
context-modeMost PopularTrending
FAQ
FAQ
What is the difference between causal-memory and context-mode?
Both causal-memory and context-mode are in the Memory & Context category. causal-memory has 101 stars, while context-mode has 31.8k stars.
Which is better, causal-memory or context-mode?
The best choice depends on your use case. Choose causal-memory if Preventing Repeated Mistakes: Agents can recall past `decision → outcome` causal edges, avoiding re-fixing the same bug or repeating past failed architectural choices., and context-mode if Deep repository research and analysis (e.g., architecture, contributors, issues).
Is causal-memory free or open source?
Yes, causal-memory is open source on GitHub (Apache-2.0).
Is context-mode free or open source?
Yes, context-mode is open source on GitHub (Elastic License 2.0).
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