headroom
★ 77.5k
vs
mneme
★ 171
headroom vs mneme
headroom: Headroom compresses everything your AI agent reads — tool outputs, logs, RAG chunks, files, and conversation history — before it reaches the LLM. It achieves the same answers with a fraction of the tokens.; mneme: dsh-mneme is a DeepSeek Harness plugin providing sophisticated cross-session memory for LLMs. It not only stores information but actively manages it through features like background deduplication, conflict resolution, and auditable history, ensuring AI remembers past interactions.
01
TL;DR
headroomMemory & Context · ★ 77.5k
When to choose:
- Long tool output, logs, JSON responses or RAG chunks are driving up cost or hurting answers.
- You want compression without code changes: run it as a local proxy, an MCP server, or by wrapping Claude Code, Codex or Cursor.
- Compression must run locally, with originals cached so the model can retrieve the full text.
When to skip:
- Your agent's problem is missing or outdated docs, not too much context: a docs server fits better.
- You cannot add a component that must keep running and may add latency.
- Your tasks cannot tolerate lossy compression: verify answer quality on your own work first.
mnemeMemory & Context · ★ 171
Continuing project discussions across multiple sessions without repetition.
02
Side-by-Side Comparison
Field
headroommnemeCategory
Memory & Context
Memory & Context
Stars
★ 77.5k
★ 171
License
Apache-2.0
MIT
Install Command
pip install "headroom-ai[all]"
dsh plugin --profile web add @modusensus/dsh-mneme && dsh web
Updated
1d ago
2d ago
Open Source
Yes
Yes
Tags
Context Compression, Token Optimization, AI Agents
LLM Memory, Cross-Session Context, DeepSeek Harness Plugin
03
Features
headroom01In-app library for compression (Python/TypeScript)
02Zero-code-change proxy mode
03One-command agent wrapping for various AI agents
04Cross-agent shared memory and auto-deduplication
05Reversible compression (CCR) with original content retrieval
mneme01Replayable and Auditable Memory
02Conflict Resolution with Human Oversight
03Agent and Workspace Memory Isolation
04Offline-first Local Semantic Search
05Automatic Background Memory Consolidation
04
Use Cases
headroom↳Reduce LLM token usage and API costs for AI agents.
↳Enable shared context and memory across multiple AI agents.
↳Optimize coding agents by compressing tool outputs, logs, and RAG chunks.
↳Maintain full data fidelity with reversible context compression.
mneme↳Continuing project discussions across multiple sessions without repetition.
↳Persisting AI's understanding of user preferences and coding habits long-term.
↳Automatic archiving and retrieval of organized research notes after closing chat windows.
05
Best For
headroomMost PopularEssential
mneme—
FAQ
FAQ
What is the difference between headroom and mneme?
Both headroom and mneme are in the Memory & Context category. headroom has 77.5k stars, while mneme has 171 stars.
Which is better, headroom or mneme?
The best choice depends on your use case. Choose headroom if Reduce LLM token usage and API costs for AI agents., and mneme if Continuing project discussions across multiple sessions without repetition..
Is headroom free or open source?
Yes, headroom is open source on GitHub (Apache-2.0).
Is mneme free or open source?
Yes, mneme is open source on GitHub (MIT).
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