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tnm/zclaw

Your personal AI assistant at all-in 888KiB (~35KB in app code). Running on an ESP32. GPIO, cron, custom tools, memory, and more. observed · 2026-08-28

github.com/tnm/zclaw · homepage · C · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

66/100

  • Activity 82
  • Release rhythm 75
  • Longevity 14
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 4
  • age_days: 198
  • days_rel: 164
  • days_push: 108
  • n_releases_24m: 4

Full methodology

Adoption not part of the score

2221 stars · 192 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

zclaw is a personal AI assistant firmware written in C that runs entirely on ESP32 microcontrollers within a strict 888 KiB all-in firmware budget. It maps natural-language chat (via Telegram or a web relay) to on-device tool calls including scheduled tasks, GPIO control, sensor reads, persistent memory, and user-defined custom tools.

Use cases

  • run an AI assistant on an ESP32 microcontroller
  • control GPIO pins with natural language commands
  • schedule recurring tasks like watering plants from a chat bot
  • build a tiny self-contained LLM agent on embedded hardware
  • remind me in 20 minutes via a Telegram bot
  • read DHT11/DHT22 sensors and remember values on-device
  • flash a minimal AI firmware under 1MB on ESP32-C3/S3/C6

When to choose

  • you want a self-hosted AI assistant running entirely on cheap ESP32 hardware
  • you need natural-language control of GPIO, relays, or sensors without a separate server
  • you care about an extremely small firmware footprint (888 KiB all-in)
  • you want cron-like scheduling and persistent memory on a microcontroller

When to avoid

  • you need heavy LLM inference on-device - it relies on external OpenAI-compatible or Ollama backends
  • you need a general-purpose home automation hub with broad device integrations
  • your project targets non-ESP32 microcontrollers or requires large TLS feature sets
  • you want a managed cloud product rather than flashing and provisioning your own board

Facets

application · maturity active

agent-framework llm-inference chatbot scheduling iot embedded developer-tools artificial-intelligence iot embedded-systems chatbots hardware embedded iot windows cli esp32 firmware tiny-llm-agent gpio telegram-bot c freertos esp-idf home-automation microcontroller ai-agents automation linux macos

4 sources

Member repositories

RepositoryRoleHealth v2
tnm/zclawmain66

For agents

markdown · JSON · MCP: product_card(name="tnm/zclaw")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem