headroom
★ 77.3k
vs
okf-agent-memory
★ 827
headroom vs okf-agent-memory
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.; okf-agent-memory: OKF Agent Memory provides a domain-neutral, Git-native persistent project memory for AI agents, leveraging the Dual-Memory Agent Architecture to prevent context bloat and memory rot. It uses an ultra-compact behavioral codex and a queryable OKF v0.2 knowledge bundle, with blazing-fast, zero-cost local retrieval.
01
TL;DR
headroomMemory & Context · ★ 77.3k
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- Your agent's problem is missing or outdated docs, not too much context: a docs server fits better.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.
okf-agent-memoryMemory & Context · ★ 827
Software Engineering: Managing architecture decisions, code references, and operational constraints.
02
Side-by-Side Comparison
Field
headroomokf-agent-memoryCategory
Memory & Context
Memory & Context
Stars
★ 77.3k
★ 827
License
Apache-2.0
MIT
Install Command
pip install "headroom-ai[all]"
git clone https://github.com/okf-memory/okf-agent-memory.git && cd okf-agent-memory && make build
Updated
Today
1d ago
Open Source
Yes
Yes
Tags
Context Compression, Token Optimization, AI Agents
AI Agents, Persistent Memory, Knowledge Base
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
okf-agent-memory01Dual-Memory Cognitive Architecture (DMAA) to eliminate prompt bloat.
02Blazing fast performance with in-memory BM25 search (<300µs) and graph validation (~4ms).
03100% Git-native, zero vendor lock-in, and zero API costs for memory retrieval.
04Built on Google's Open Knowledge Format (OKF) v0.2 for standardized agent knowledge.
05Solves context bloat and memory rot through progressive disclosure and Search-Before-Write principle.
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.
okf-agent-memory↳Software Engineering: Managing architecture decisions, code references, and operational constraints.
↳Scientific Research & Literature Reviews: Organizing and querying research findings and insights.
↳Coaching & Operations: Storing client session history, ethical guidelines, and runbooks.
↳Multi-Agent Collaboration: Providing a shared, auditable knowledge base for autonomous agents.
05
Best For
headroomMost PopularEssential
okf-agent-memoryHidden Gem
FAQ
FAQ
What is the difference between headroom and okf-agent-memory?
Both headroom and okf-agent-memory are in the Memory & Context category. headroom has 77.3k stars, while okf-agent-memory has 827 stars.
Which is better, headroom or okf-agent-memory?
The best choice depends on your use case. Choose headroom if Reduce LLM token usage and API costs for AI agents., and okf-agent-memory if Software Engineering: Managing architecture decisions, code references, and operational constraints..
Is headroom free or open source?
Yes, headroom is open source on GitHub (Apache-2.0).
Is okf-agent-memory free or open source?
Yes, okf-agent-memory is open source on GitHub (MIT).
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