Honcho
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Introduction
AI-native memory platform providing stateful context for agents with continual learning and token efficiency.
Listed on
September 8, 2026
What is Honcho?
Honcho is an AI-native memory platform designed to give stateful agents persistent, reasoning-based memory. It goes beyond simple storage and retrieval by continually learning from interactions, delivering curated context that saves tokens and improves user experience. Honcho is model-agnostic and can be integrated with various AI frameworks and tools.
How to use Honcho?
- To use Honcho, developers can start by installing the Honcho CLI via npx or as a Claude Skill. For specific integrations, install plugins for Claude Code, OpenAI Codex, OpenClaw, Hermes Agent, or DeepSeek Harness. After setup, write messages to Honcho sessions and call context() to retrieve formatted conversation context for LLM integration.
Core features of Honcho
- Continual learning with automatic reasoning on every message
- Token-efficient context delivery (60-90% token savings)
- State-of-the-art performance on LongMem, LoCoMo, and BEAM benchmarks
- Model-agnostic: works with OpenAI, Anthropic, custom models
- Unlimited retrieval with granular control (search, token budgets, summaries)
- On-demand advanced reasoning via .chat() with tiered resource levels
- Integrations for Claude Code, OpenAI Codex, OpenClaw, Hermes, DeepSeek Harness
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