// agents · plastic-labs/honcho

honcho

honcho é um projeto de agentes de IA de código aberto de plastic-labs (plastic-labs/honcho no GitHub). Tem 7.536 estrelas no GitHub e 928 forks, é publicado sob a licença AGPL-3.0 e foi atualizado pela última vez no GitHub em 8 de outubro de 2026.

Honcho — Plastic Labs' memory library for stateful agents that learn about their users over time.

★ 7,5 mil estrelas⑂ 928 forksAGPL-3.0atualizado out 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto

Dados do projeto

Estrelas no GitHub
7.536
Forks
928
Licença
AGPL-3.0
Última atualização no GitHub
8 de outubro de 2026
Categoria
Agentes de IA
Tipo de ficha
Guia de instalação completo
Site oficial
Official site
// como funciona

Como funciona

  1. Clarify your goal

    Decide managed versus self-hosted, and model your world as peers and sessions — typically your users and your agent as peers exchanging messages.

  2. Get the project

    Clone plastic-labs/honcho from GitHub (or use the install path in the run steps below) and skim its README for the parts relevant to your goal.

  3. Install and configure

    Install the SDK for your language; for self-hosting, clone the repo and start it with Docker Compose, then point the SDK at your local base URL.

  4. Run your first task

    Store a few messages on a session, let background reasoning run, then query Honcho for what it knows about that peer and inject the context into a prompt.

// recursos

Por que as pessoas gostam tanto

The Honcho loop

Store messages, let asynchronous background reasoning build understanding, query it, and inject prompt-ready context into any model.

Peers and sessions model

Memory is organised around peers (users, agents) and their sessions, rather than a flat chat log.

Managed or self-hosted

Use the managed api.honcho.dev service, or self-host from source with Docker Compose or a local dev setup.

Python and TypeScript SDKs

pip install honcho-ai, or npm install @honcho-ai/sdk, with equivalent workflows in both languages.

Agent-tool integrations

Documented integrations add Honcho memory to Claude Code, Codex and Cursor via dedicated packages and install scripts.

Built for stateful agents

Aims at continual, cross-session memory and context engineering rather than one-conversation chat history.

Advertisement
// execute você mesmo

Execute você mesmo

  1. Clone the repository

    Get the source from the official GitHub repository for honcho.

    git clone https://github.com/plastic-labs/honcho.git
    cd honcho
  2. Install the SDK

    Install the Python SDK as the README quickstart shows (TypeScript: npm install @honcho-ai/sdk).

    pip install honcho-ai
  3. Or self-host from source

    Clone the repo and start the full service locally with Docker Compose, then set HONCHO_URL or base_url to your instance.

    git clone https://github.com/plastic-labs/honcho.git
    cd honcho
    docker compose up  # see README self-hosting section
// casos de uso

O que você pode criar

Advertisement
// perguntas frequentes

Perguntas frequentes

Who maintains honcho?

plastic-labs (Plastic Labs), through the plastic-labs/honcho repository, with docs at honcho.dev/docs.

Is honcho free to use?

Yes — the project is open source under the AGPL-3.0 license as recorded for this listing. See the license terms for any conditions on redistribution.

Does honcho need a paid API key?

The managed service uses api.honcho.dev (account/API key). Self-hosting is free under AGPL-3.0 and runs on your own infrastructure; reasoning uses models you configure there.

How does Honcho compare to storing chat history in my own database?

A database stores raw history; you still build recall, summarisation and context assembly. Honcho adds the reasoning layer — it processes messages in the background so queries return understanding and prompt-ready context, not just logs.

How do I get started with honcho?

Clone the repository (or use the documented installer), follow the install and configure steps on this page, and run the smallest real task first — store a few messages on a session, let background reasoning run, then query Honcho for what it knows about that peer and inject the context into a prompt.

// continue explorando

Ferramentas semelhantes

Agentes de IA

hindsight

Agent memory that learns — so your agents get smarter over time.

★ 47,0 mil estrelasMIT
Ver o guia →
Agentes de IA

letta

Stateful AI agents with memory that learns and improves.

★ 25,1 mil estrelasApache-2.0
Ver o guia →
Agentes de IA

mex

Team memory for engineers and their AI agents.

★ 1,8 mil estrelasMIT
Ver o guia →
Agentes de IA

langmem

LangMem: long-term memory primitives for LangGraph agents that learn and adapt from conversations.

★ 1,7 mil estrelasMIT
Ver o guia →
Agentes de IA

graphiti

Real-time knowledge graphs that give agents a memory with structure.

★ 31,5 mil estrelasApache-2.0
Ver o guia →
Agentes de IA

Agent_Memory_Techniques

30 runnable notebooks teaching everything about agent memory.

★ 1,1 mil estrelasApache-2.0
Ver o guia →
// alternativas

Alternativas em Agentes de IA

Os outros projetos de Agentes de IA com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se honcho não for o ideal para você.

// mais em agents

Mais em Agentes de IA

Projetos de Agentes de IA próximos no catálogo, os mais próximos em estrelas de honcho: continue explorando dos dois lados dele.

Baixe o honcho

Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.